Encouraging the Use of Underutilized Marine Fishes by Southeastern U.S. Anglers,
Part I: The Research
JEFFREY C. JOHNSON, DAVID C. GRIFFITH, and JAMES D. MURRAY
Introduction
Every year, millions of fishermen discard, release, or unnecessarily ruin and waste millions of pounds of saltwater fish that they consider poor eating or inedible. The National Marine Fisheries Service (NMFS) estimates that, from the Atlantic and Gulf coasts alone, recreational fishennen catch over 33 million fish belonging to such underutilized groups such as jacks, catfishes, tunas, and skates and rays (USDOC, 1980). Most of these fish are discarded or released in favor of more highly desired and perhaps overfished species like grouper, snapper, and king mackerel (Bell, et a!. 1982). This underutilization of potentially valuable marine resources occurs at a time: I) When increased real and perceived pressure is being placed on preferred marine resources by both recreational and commercial fishennen, both of whom use increasingly more efficient technologies to locate and catch fish; and 2) with political conflicts between marine recreational fishermen and commercial fishermen
ABSTRACT-Ths paper is the first of a two-part series which describes and discusses the integration of research and extension increase 10 the use of nontraditional fishes among marine recreational fishermen in the southeastern United States. Recreational fishermen within this region target and use or reject fish on the basis of a variety of criteria. Many fish caught incidentally are discarded because of myth, rumor, or perceived negative characteristics that mask the species' positive values. To discover the factors influencing the angler's evaluations concerning the desirability of fish that ultimately af
over access to and claim over marine resources (Berkes, 1984). Presumably, increasing the share of underutilized species in the total recreational catch will aid in reducing both biological pressures and subsequent political conflicts.
In 1983, we began investigating southeastern U.S. marine recreational fishermen's beliefs about species of saltwater fish in an attempt to isolate the specific criteria upon which they base their decisions to use or reject a fish. This was part of a 3-year program to increase demand for underutilized species among marine recreational fishennen of the U. S. southeast. During the first year we empirically investigated fishermen's perceptions concerning fish and developed informant-based models, which fonns the core of this paper. Based on this earlier research, we have subsequently attempted to enhance the images or to "repackage" underutilized species with an educational program consisting of brochures, posters, recipes, and a slide/ tape presentation.
In this paper, Part I, we present a brief
fects their decision to accept or reject a particular species, we collected judgedsimilarity and belief-frame comparison data in Florida, North Carolina, and Texas, analyzing these data with the use of multidimensional scaling, hierarchical clustering, and entailment analysis. We briefly describe the use of these procedures in providing for a svstematic understanding offishermen's perceptions concerning fish and discuss the implications of our findings for the development of educational materials directed at enhancing the image of certain underutilized species among marine recreational fishermen.
description of the research and its findings, focusing on the implications of this work in the development of the educational program. The philosophy, dynamics, and achievements of the educational program are the focus of Part II (Murray et a!., 1987).
Methods
Data Collection and Analysis
In exploring the perceptions that recreational fishermen have of various marine species, we incorporated methods and theories from the fields of anthropology and consumer research. Two techniques we used are multidimensional scaling (MDS) (Kruskal, 1964) and hierarchical clustering (HCL) (Johnson, 1967). Generally, any items that can be compared on the basis of similarity or dissimilarity can be visually represented as points spatially distributed in euclidean space (MDS) or as items grouped together hierarchically as a taxonomic structure (HCL). Both techniques display relationships among items or stimuli (e.g., different kinds of fish) based on measures of similarity/dissimilarity (a more detailed discussion is given by Romney et a!., 1972).
Jeffrey C. Johnson is Associate Scientist and David C. Griffith is Assistant Scientist with the Institute for Coastal and Marine Resources. East Carolina University. Greenville. NC 278584353. James D. Murray is Director. Marine Advisory Services. UNC Sea Grant College Program, North Carolina State University, Raleigh. NC 27695 This research was funded by the National Marine Fisheries Service. NOAA. under the Saltonstall-Kennedy Program Contract No. NA83-WC-H-OOI6. Portions of this paper were derived from Johnson and Griffith (1985) and Johnson et al (1986).
Marine Fisheries Review 122
We used these techniques to explore fishermen's judged similarities between selected saltwater fishes. To accomplish this, we asked fishermen to sort cards with pictures and names of fish on them into piles on the basis of how they perceived species to be similar to one another. We then asked them to explain their groupings. Consequently, the common group memberships among species, the relationships among the groups, and the derived similarity measures between the species were determined by the manner in which fishermen sorted species into piles.
Two methods for deriving similarity data from the pile sorts were explored. The first is based on information theory and tends to emphasize minor distinctions made by subjects (Burton, 1972). The second is based on the summing of co-occurrence of items (stimuli) in a pile across all subjects (Weller, 1984). Comparisons and tests of both techniques convinced us that, for our purposes, the latter provided a better measure of similarity for use with these statistical procedures.
The information derived from these methods is necessary to first identify relationships among saltwater species as perceived by recreational fishermen, and to determine the characteristics which make saltwater species desirable or undesirable. Discovering the relative position of underutilized species within a multidimensional scaling's configuration of points is analogous to the concept of "product positioning" in marketing research.
The concept of "product positioning" refers to the discovery of the structure of a particular product domain (e.g., different kinds of coffee) and the development and packaging of new products or old ones for new markets based on identification of yet unexploited portions of this particular domain. A good example of this is the development of a new popular brand of coffee with the use of the above methods (Stefflre, 1972).
We used one further method to identify and understand the ways recreational fishermen think about their prey. This involved constructing sentence frames (belief-frames) based on interviews with recreational fishermen from each study area. Recurring descriptions of both tra
49(2), 1987
diational and nontraditional recreational species (e.g., fighting characteristics, eating characteristics, etc.) were used to produce fill-in-the-blank sentences. In subsequent interviews, subjects were asked to provide the species (from an appropriate list) associated with the attribute implied in each sentence, such as "You cannot eat because it has worms."
These species/belief-frame comparisons were incorporated into an "item-byuse" matrix (Stefflre, 1972) organized in a species-by-attribute form for each of the study areas. This is similar to a method used in the study of food snacks and their attributes with respect to when they are eaten (Stefflre, 1972). Each species/belief-frame matrix was sorted by rows and columns so that rows that were similar to one another were near one another; and columns that were similar to one another were near one another. This was accomplished through a combination of techniques used by both D' Andrade et a!. (1972) and Stefflre (1972). D' Andrade et a!. (1972) computed Pearson correlations for belief-frames across items and for items across belief-frames. These coefficients represented similarity measures and were clustered for rows and columns through the use of a hierarchical clustering scheme (Johnson, 1967).
Stefflre (1972), on the other hand, produced a similarity measure based on rowrow and column-column similarity in patterning. For our purposes, however, we use a computationally equivalent algorithm which alleviates the need for transposing row and column vectors. These similarities were then used in an iterative process based on "linear equivalence chains" to sort rows and columns on the basis of similarity (Stefflre, 1972).
In this analysis, row-row and columncolumn similarities were derived with the use of the computationally equivalent version of Stefflre's algorithm discussed above. These similarity measures for both rows and columns were subjected to HCL to obtain the sorted species/belief-frame matrices for each region.
Data from the belief-frame comparisons can also be modeled in terms of implicational or logical relationships (D' Andrade, 1976; Schoeptle et a!., 1984; White et a!., 1977; White and Mc
Cann l ). The structure of these relationships, or the entailment structure, is obtained through a multivariate contingency analysis of paired dichotomous variables similar to Guttman scaling. The logical or implicational relations are modeled in an "If A then B" (visualized in Figures 10-13 as A<--------B) form and are not symmetrical. It allows for both complete and partial orderings in which relationships are transitive. Two other forms are possible. The first is the equivalence relation, which takes the symmetrical form of "A = B" and the contrast relation of the form "If A then not B." A more detailed description can be found in D' Andrade (1976) and White et a!. (1977).
Sampling
An important consideration for the application of these techniques is the assumption that there are shared understandings, beliefs, or pools of information among respondents and the cultures or subcultures of which they are a part, in the same way that a handful of English speakers can provide a complete grammar of English. For example, a review of studies that employed MDS interviewed between 10 and 50 subjects with one using as little as 5 while another used as many as 600 in a national survey (e.g., D' Andrade, 1976; Romney, et a!., 1972). Stefflre (1972:214) stated: "This kind of data stabilizes with fairly small samples of respondents (N=30-60)." These techniques are not as reliant upon random selection or sample size for gaining statistical significance as would be found among other statistical procedures. Rather, it is more important in these procedures to sample subjects who have a shared understanding of the domain under study.
Like most anthropologists, we assume that members of human societies share beliefs and ways of behaving. These shared understandings and actions are what constitute "culture." In every human society, culturally coherent pools
IWhite, D. R., and H. G. McCann. 1981. Material and probablistic entailment analysis: Multivariate analysis of "If ... then" statements in cultural systems. Manuscr. on file at School Soc. Sci., Univ. Calif., Irvine.
123
of information and knowledge are transmitted from individual to individual through processes of enculturation or socialization. In this research, our interests lie in describing the social behavior of recreational fishermen that may be directly attributable to the ways they categorize or rate fish.
All beliefs and perceptions will be affected by the degree to which subjects have been socialized into a particular system. In other words, an II-year-old's understanding of their kinship system is less robust than, for example, his or her 30-year-old father's. We assume, of course, distinct parameters defining the nature and extent of knowledge about a particular domain. This knowledge is shared to varying extents among all members of the system-from a normative standpoint-and is passed on to new members through a socialization process. In this case, an individual who is new to recreational fishing will generally be socialized as a "recreational fisherman" through his or her experiences and subsequent discussions with more integrated members of the recreational "subculture" (e.g., at parties, bars, at home, on boats, on piers, etc.)2 These assumptions guided our sample selection, in that we were interested in locating relatively experienced fishermen.
For the most part, fishermen in this
ZThis is not to say that the population of U.S. marine recreational fishermen is homogeneous. consisting of a single language or ethnic group whose attitudes toward fish are uniform. In fact, there are segments of the total recreational fishing population to which our findings may not apply. For example, it could be argued that because the fishermen in our sample are overwhelmingly white males, drawn from fishing clubs, our findings cannot be extended to black, Hispanic, Korean, Vietnamese or other minority recreational fishermen in the United States. The basis for this argument lies in the findings of linguists and other social scientists, who argue that distance differences in linguistic behavior, socialization, and ethnicity between whites and these other ethnic groups result in different meanings, perceptions, and beliefs about the things of this world. It is important to note, however, that is has been shown more recently by Romney, et al. (1979) that ethnic enclaves in the United States may show more in common cognitively with the mainstream of American culture than is evident from casual observation. This seems to point to the importance of length of exposure to American popular culture (e.g., television, radio. etc.) and interaction with other social groups in the United States.
study belonged to non-species-specific fishing clubs. Four such clubs were identified for data collection. These were located in and drew their members from east Florida, west Florida, Texas, and North Carolina. About 30 fishermen from each area were interviewed. A fifth sample of nonfishing club members was taken from the piers and other fishing spots in east Florida for comparative purposes (N = 10)3. Some selected characteristics of the fishing club members and their fishing and fish preparation behaviors are included in Table 1.
Results
Hierarchical Clustering Analysis (HCL)
Table 2, a summary of the results of the HCL for the four regions4 , shows that the same general categories, presented along the left-hand side of the chart, were found in all regions. These categories reflect the general ways that marine recreational fishermen in each of the areas group species of saltwater fish. The boxes with the names of the fish represent the clusters of species that fishermen put together most often in the sorting tasks. As Table 2 shows, the general criteria that fishermen used to categorize species were:
I) Sportfish, or species that are fun or exciting to catch. In east and west Florida, fishermen differentiated between good-eating and poor-eating sportfish, while neither Texas nor North Carolina fishermen made these finer distinctions.
2) Meatfish, or fish that are good to eat. In addition to the meatfish designation, fishermen in all four regions separated their meatfish in terms of the ranges or habitats of the species. In all regions, the groupers and snappers were placed together and often described as "goodeating reef fish," while trout, bluefish,
3To address the question of how similar fishing club members are to nonclub members, we compared responses from club and non-club members in east Florida with Pearson (0.78) and Spearman (0.63) correlation coefficients. These were significantly similar at the 0.000\ level for both tests. 4Clusterings were produced using the SAS average linkage procedure.
red drum,. etc. were described as "fish you can eat that you catch in the surf or from a pier."
3) A third category of lower quality or less well-known fish, also divided on the basis of range, begins the categories that contain species many fishermen reject. Texas fishermen lumped these species in with their "trashfish," while some fishermen in the other three areas acknowledged the utility of some of these species as fish they would use for bait. Most of these species, however, were perceived to possess one or two negative qualities, as will be seen below in the item-by-use matrices. These qualities made them less desirable than the fish in the second category.
4) Trashfish. Fishermen saw these species as the sea's least desirable. They used derogatory terms, such as "odd-ball species," "dangerous fish," "pisswinks," and "garbage," to describe these species. None were targeted for food or sport. A few fishermen had eaten puffer, calling it "the chicken of the sea," and an occasional favorable statement was made about gafftopsail catfish, but generally these fish were considered low on the scale of marine fishes.
Fishermen rejected these species for various reasons. In a few cases, the ugliness of these fish were cited. Others offered explanations that were, at least superficially, more reasonable. Searobins and puffers were said to be "all head and no meat"; puffers, poisonous; sea catfish, poor-tasting scavengers and dangerous to handle because they could use their spines like spears. Fishermen told of bad experiences with catfish, ray stingers, and the spines of searobins.
Species in this last category offended the fisherman's sense of what a fish should be-a scaled, silver, or colorful fish shaped like a grouper or cobia. But fish in category 4 have bumps, wings, stingers, blotchy and smooth skins like salamanders, and spines and whiskers like porcupines. They act strange, puffing up, grunting, or flying when tossed in the air.
One of the primary reasons for rejecting these species, then, is that fishermen tend to associate appearances and odd behaviors with undesirable characteristics. These findings are reaffirmed below in
Marine Fisheries Review 124
Table 1.-Selected characteristics of fishing club members.
Club membership data
Length of membership (years)
Age
Education in years Percent without HS diploma Percent with HS diploma (only) Percent with <4 years of college Percent with 4 years of college Percent with advanced degrees
Percent who own their own boats
Percent who clean, scale, etc. their fish themselves 0-20% of time 21-50% of time 51-99% of time 100% of time
Percent who have someone else clean, scale, etc. their fIsh 0-20% of time 21-50% of time 51-99% of time 100% of time
Percent who cook their own fish 0-20% of time 21-50% of time 51-99% of time 100% of time
Percent who have another person cook their fish 0-20% of time 21-50% of time 51-99% of time 100% of lime
Cooking styles-1 % of population who: Broil Deep fry Pan fry Bake Barbeque/gnll Smoke Other
the entailment analysis. The notable exception to this is flounder. With two eyes on one side, often blotchy skin, and a flat body like a skate or ray, the flounder qualifies as unusual-looking fish. In fact, one fisherman told of tossing a flounder back before he learned from another fisherman what it was. The nearly universal utilization of flounder among marine recreational fishermen suggests that a fish which is good tasting and easy to clean will be utilized even if it does not approach the fishermen's ideal.
5) Sharks and dogfish, for obvious reasons, were lumped together by nearly every fisherman in the sample. For many, they comprised yet another group of trash fish .
Figure I converts the information from Table 2 into a tree diagram demonstrating
49(2), /987
East Florida West Florida North Carolina Texas
Mean Median Mode % Mean Median Mode % Mean Median Mode % Mean Median Mode %
6.87 7.5 10 5.13 4.12 3 2.3 2 3.7 3.3 3
49.6 44.4 44 48.7 52 52 42.3 39 28 41.2 40 36
15.6 15 16 14.3 14.2 16 17.3 16.4 16 17 16.2 16 4.2 0 0 5
20.8 26.1 6.9 0 29.1 34.7 6.9 5 25.0 30.4 37.9 55 20.9 8.7 48.3 35
91.7 56.5 60 70
96.0 100 93.3 90 4.0 0 0 0
12.0 4.3 3.3 0 8.0 0 0 10
72.0 95.7 90.0 80
28.0 4.3 6.6 20 8.0 0 0 10
16.0 0 33 0 4.0 4.3 0 0 0 0 33 10
72.0 78.3 86.7 55 8.0 17.3 99 5
12.0 17.3 20.0 10 16.0 12.9 19.8 5 36.0 30.4 36.7 35
600 73.9 63.3 65 8.0 8.7 13.2 5 8.0 26.1 26.6 10
20.0 26.1 13.2 5 24.0 13.0 10.0 45
59.1 783 73.3 55 59.1 65.2 73.3 65 22.7 34.8 16.7 5 31.8 39.1 40.0 30 22.7 30.4 36.7 15 31.8 26.1 10.0 5
4.5 4.3 3.3 5
the hierarchical levels at which the species are more closely or distantly related in terms of perceived and objective criteria. While the tree diagram (Fig. I) and Table 2 both show that there is a great deal of agreement h~tween regions in terms of the criteria used to classify saltwater fish, they also show that there is a great deal of overlap between regions in terms of the actual individual species that meet these criteria of sportfish, meatfish, and so on.
We draw three basic points from this information. First, in some cases, fish that are rejected by most fishermen (underutilized species) fall into categories with fish that are preferred. For example, while the poor-eating sportfish category in east and west Florida contains mostly underutilized species like amberjack,
crevalle jack, etc., it also contains the highly sought tarpon; in North Carolina we find the generally undesirable pinfish and pigfish in the same pile with desirable croaker and spot.
Second, some fish that fall into rejected categories in one area fall into preferred categories in others. Mullet in west Florida is perceived as a higher quality fish than it is in east Florida; in Texas, mullet is considered a trashfish. Smaller species such as croaker and spot, while highly desired in North Carolina, tend to be scorned in east Florida or used only for bait.
Finally, and related to the second point, we see that the sizes and compositions of the categories vary greatly between regions. Texas has the largest trashfish or undesirable category and
/25
North Carolina the most meatfish, for ex Table 2.-Species clusters by major categories for the four regions: East Florida, West Florida, North Carolina, and
ample. This information tells us that, most im
portantly, some species have been classified as preferred or undesirable on the basis of local information, rumor, and the general processes that accompany being socialized into recreational fishing, rather than on the basis of more objective criteria. We will see below, in the itemby-use matrices, that fishermen consistently said "most people don't eat" about fish that they had never tried eating. In many cases it's obvious that a fish is underutilized in one region primarily because there's no tradition of utilization. Fishermen need only be informed that these fish are perfectly edible, and even good, and they will probably begin utilizing them.
One final point to be made here is that the availability of species tends to be a big factor in whether a fish is targeted or rejected. For instance, smaller species get worse ratings in east Florida than in North Carolina because bigger fish are perceived to be more plentiful and easier to catch in east Florida.
Multidimensional Scaling
Figures 2-5 present the MDS configurations for each of the regions5. The findings from the clustering analysis are complemented by the MDS analysis. Whereas in the clustering analysis we found that the two common categories of meatfish and sportfish came up in every region, in the MDS we found that the most common dimensions in all regions were:
I) Edibility (from good-eating fish to bad-eating or inedible fish) and
2) Sportfish (from large, strong fighting fish like wahoo and tarpon to the smaller, panfish types such as spadefish, searobins, and so on).
While these two dimensions appeared in all regions, they were clearest in east and west Florida and least clear in orth Carolina. In orth Carolina, there were a number of other criteria that muddled the
5Stress figures for the scalings in three dimensions were: Texas. 0.171; east Florida. 0.170: west Florida. 0.157; and North Carolina. 0.145
Texas.
Major category East Florida West Florida North Carolina Texas
I. Sportfish Amber)ack Amberjack Amberjack Amberjack 8. wPoor·eating." Barracuda Barracuda Barracuda Barracuda2
Tarpon Tarpon Cobia Pompano2
Blue runner Blue runner Linle luna Snook Crevalle jack Crevalle jack Dolphin Tarpon Ladyf,sh Ladyfish Spanish mackerel Cobia Rainbow runner Wahoo Spanish mackerel
King mackerel Wahoo Snook2 King mackerel Tarpon Atlantic mackerel
b. "Good-eating." Cob,a Bluefish Dolphin Wahoo Spanish mackerel Cobia King mackerel Dolphin Wahoo Pompano
Snook2 King mackerel Spanish mackerel
II. Meatfish Black sea bass Black sea bass Black sea bass Jewfish a. Ollshore Jewflsh Nasau grouper Red snapper Red snapper
Gray snapper Red snapper Warsaw grouper Black grouper Red snapper Warsaw grouper Nasau grouper Schoolmaster Schoolmaster snapper Scamp Munon snapper Warsaw snapper Munon snapper Lane snapper Red porgy Nasau grouper Black grouper Jewflsh Jewfish Red grouper Nasau grouper Red grouper Gray snapper Lane snapper Lane snapper Black grouper Lane snapper Gray snapper Red grouper Schoolmaster snapper MuMon snapper Warsaw grouper Black grouper
b. Inshore Bluefish Summer flounder Bluefish Summer flounder Snook Mullet Mullet Sand Irout Southern klngfish Sheepshead Sfriped bass Weakfish Northern klngf,sh Weakfish Weakfish Red drum Summer flounder Sand trout Red drum Southern flounder S::md troul Beach whiting Sponed Irout Sponed Irout Pompano Sponed trout Stnped bass Red drum Croaker Red drum Southern flounder Summer flounder Beach wh,ting Pompano Sponed trout Spot Southern flounder Southern flounder Weakfish Pigfish
Sheepshead White perch Pintish Bunerfish Silver perch Southern kingfish Beach whiting
III. Lower quality or Sheepshead Queen triggerfish Spadefish No Texas clusters fit less well·known meat Tnpletail Schoolmaster snapper Silver Jenny2 these designations. fish3 Scamp Tripletail Tautog/Blackfish
a. Ollshore Gag Gray triggerfish Queen triggerfish Queen trlggertish Gag Scamp2 Gray tnggerf,sh Mutton snapper Gray triggerfish
Gray snapper Tripletail Gag
b. Inshore4 Croaker Croaker Blue runner ("BaiHish") White perch Northern kingfish2 Northern kingfish
Flod,a grunts Silver perch Crevalle jack P'gf,sh Southern puller Rainbow runner Silver perch Pigfish Ladyfish Spot Spadefish Spadelish White perch Mullet Spot BuMerflsh Bunerfish Plntlsh Silver Jenny Sliver Jenny Pinfish
Grunts
(Continued on next page.)
dimensions of edibility and sport, such as Florida (Fig. 2). for example, we can see the size. shape, and habitats of the fish. that the flounders, snappers, and
Examining the MDS figure for east groupers fall to one side of the axis at the
Marine Fisheries Review /26
Table 2.-Conlinued.
Major category East Florida West Florida North Carolina Texas
IV. Trashfish5 Sea catfish Southern putfer Bighead sea robin Smooth puffer Northern sea robin Allantic stingray Gafftopsail caltish
Sea catfish Northern sea robin Gafftopsall Caltish Smooth puffer Bighead sea robin Atlanttc stingray
Sea catfish Smooth puffer Northern sea robin Gafftopsail catfiish Bighead sea robin Atlantic needlefish Red hake Southern puffer Allantic stingray
Black sea bass Queen triggertish Grunts Silver perch Spot Silver Jenny Smooth puffer Gag Northern sea robin Scamp Pinfish Bighead sea robin Southern puffer Blue runner Spadetish Ladyfish Pigfish Northern kingfish Rainbow runner Gray triggertish
Bluefish Sea caltish Crevalle jack Southern kingfish Mullet Gafftopsail catfish Croaker Sheepshead Beach whiting Striped bass Tripletail Stringray
V. Sharks/dogfish6 Blacklip shark (Spinner)
Dusky shark Bull shark Sandbar shark Smooth dogfish
Mako shark Lemon shark Great white shark Sixgill shark Spiny dogtish
'Neither Texas nor North Carolina differentiated between ··good·eating" and "poor-eating" gamefish. 2Not well known In this area. 3These tend to be smaller, if known, and among the inshore species are those which are usually classified as baitfish. Also. because these fish are considered lower quality as food fish, the finer distinctions based on range and sporting qualities are not so strong in differentiating species from one another in these clusters. Fishermen's lack of experience with some of these species could cause the lack of finer distinctions as well. ·Species in this category were generally not well known in North Carolina. The "inshore" mealtish designation probably does not apply here. 5Texas "trashfish" species include species which were generally not well known to Texas fishermen; perhaps a better description of these clusters would be to say that they inClude those species Texas fishermen do not care very much about, nor know much about, nor care to catch. 6With the exception of West Florida. which differentialed the dogfish trom the sharks. all the MCA results contained a cluster Including all the sharks and dogfish. ···Break within a cluster ····Break between clusters.
SALT~ATER FISH
I I
FISH YOU WOULD OR MIGHT KEEP DEFINITE REJECTS
I I~ I I
~ X ~"'" L gOOd poor 10 off 1n off snark. non-sndrk.
''1''"' ,''I'" I I ",:t"r I "..,1I!ffil I
INDIVIDUAL SPECIES
'--------------- ----------
49(2), 1987
"good-eating" extreme. As we cross the configuration, we encounter progressively less desirable species from an edibility standpoint. Thus, at the far end of the "poor-eating" fish we find such species as sharks, searobins, ladyfish, or tarpon.
The sportfish dimension can be seen from the top to the bottom of the Figure 2. The species get progressively more desirable as game fish or fish that are exciting to catch as you move from the spadefish (top) to tarpon (bottom).
The relative placement of underutilized species (dots) in relation to the utilized or preferred species (circles) was very helpful in developing the educational materials: We can visualize the similarities between species-as perceived by recreational fishennen-and then reinforce these similarities between underutilized and preferred species in the brochures, posters, and other educational materials.
The two dimensions of edibility and sport were found in all regions, but again, the precise locations of fish in relation to one another change from region to region, just as the species that fell into the clustering analysis categories varied between regions. Comparing east and west Florida, for example, we can see that the species at the extremes are almost identical: Tarpon is considered the most exciting sportfish and spadefish!pinfish the least, and the grouper/snapper species (those with white, delicate meat) are viewed in both regions as the highest qualify foodfish, and the sharks/catfish! searobins the lowest quality foodfish. Between these extremes, however, there are a few differences: Sharks are closer to tarpon in west Florida (indicating that it is considered a higher quality sportfish), and mullet and amberjack are a little closer to the "good-eating" end of the extreme in west Florida.
Figure l.-HCL major clusters in tree diagram form.
127
.c"'''''... '" '".c'-'"
c: .c: .D
'" ~: c c: '" o ':l
'" 0E ':l'" VI 0'" "'0
'- '" • ••'" •• ••"'''' • .>< ...-'" '- '
0'" .c '" "-'" .c .c .c'" '" .ca> V' '"
C1'• - - -0 0'" >'0 '" _.w 0 "'0
a>.c W:i:E· '0 :> '" "VI ~ 3:"" >,c: c: Vl __
0 • -a. .D
'" '" VI '" '"' '" •
<.;>'" '" C
>,
c:
• '"'- ...,C
.c '"'" '- '- '" '- '" • '">0- .c
Z ';.~ .- -O~
-"- - .c <.;>W'" '" '" c 0 -'" ;;:v'" •
'~ '" ~" '" :> ", 0 -;
.c'" '" '" 0 a>
"
•
""'
.c:'"c.'"""'
o E ""v -''" '"
'" •
ex '" o
'"> llJ ...
W
• ""u .'"...,
o 'o '" r..c '" e3: « O·
c o Co '
f-'"o
I-a:::
North Carolina, on the other hand, is not nearly so well defined as east and west Florida in terms of the edibility and sport dimensions. This is because North Carolina fishermen seemed to group species on the basis of a variety of criteria, including size and shape, as well as the fight of the fish or its value as a food. In any case, it is still obvious that the hardfighting fish cluster together at one end, the smaller species at the other, and that the groupers and snappers still fall into the same general region, opposite the trashfish.
Somewhat different than the other regions, Texans primarily distinguished between preferred and nonpreferred species. The three Texas favorites-spotted trout, reddrum, and flounder-all appeared together at the preferred end of the figure, and the nonpreferred species consist of both the good-fighting fish and the good-eating fish.
These differences reflect local preferences and further support our earlier contentions that the general criteria for targeting and rejecting fish remain more or less constant from region to region, while the specific stimuli that meet those
N t: criteria may vary. o
'Vi t: Item-By-Use and Entailmentll)
E 6 The results of the analysis of the itemVl by-use matrices are similar to what we >
found in the HCL and the MDS analyses. These matrices also have the added advantage of pointing out similarities and differences between the beliefs about fish (or similarities between belief-frames).
For each region, we constructed a matrix from the responses to the beliefframe comparisons. These sorted matrices are presented in Figures 6-9. Data in this form is useful for providing insights into the perceived characteristics of a fish that has an impact on its reputation or image as well as informing us of the combinations of characteristics and attributes that contribute to the clustering of species (and vice versa). In each of the figures, major clusters for belief-frames or sentence-frames are numerically identified along the rows, while major clusters for species are identified by letter along the columns.
An alternate way to view or model this data is through entailment analysis. Fig
"
"0
'""'.C.
'"
.c
.c '" '- :.:'" '" c:~ ec
.c ... '" '" ~ V<';> '" '" w
• ~~
0 CO'"..0
~
0.
c. .c:"- Vl "'''' ",.c • '- '"-'-
> llJ .- C1' "" .-0.
-.c: • '" '" ' .- V :> "''-0
- l.:)~ c.. ""'0
'" '.2n~a. ",.c"'. .- =: "" .... V"I'_"'''''
'-<.;>-'" .... 0 c: '":t ( .c :J: o ~ ~ ~ 'c
/0 ~ :; 0 \- 0."0 L • C,) E;: 0 ~
g. ~.....,OO Q\ ~ ~ """'''0"" OI..Ioo..&:.c: <1.111' CJQ.J.."
coo.Vl "''''.D c.a. '" ~ '"llJ c:::..:."'''' '" -''" '" """'"
.w v -'--'"'''' '" <.;>'"
CO E'"0 0 .c u
'"
C1'
.-c
.::;0
.c :x
",0
'" C.c 0:; "'" '"Cl.-; :>" C1' :>'" C .-c ::l: .-'" ~a)O ..... V 0
C7""-' "" C 0 ;',0C '- -0 '" '- '-"'- .c
'" c w .-.c: '" 0
.c'" 0
'" '- c ..c c,,,, :> 0 0'" c '" 00 z .c", ... 0 -'"
0. c: :> '" Vl
C ';;0 c,
0 ~ 0
0 0 " 0 '"Cl. E E'"
:>
0 -0
00 0 '- 0 0.
0 c,
.. '" ....
0 '" '0
'" '" '-'0 '" llJ c: -0
:l Cl.~ 0 :l '"
VI ...
0
llJ C,
'" ""U
>:'"C1' c
>0:
Marine Fisheries Review 128
..... ...... :>...
.&:... 0 0.&:
'" ~. ..... ... '" a. '"
.&: ... '" ...c .&:... "" en - < ... ... C
~.;;:
..~ . C
...,
o o
.&: v VI
C
.D Q ... ..... "" C .....
.&:... ... 0 :z
• • c:
.D Q ... ..... '" '" ......&:.,. ...
~ lD ...
:> a.
.....c
.&:... :> 0 VI
.&:
"" "oJ ........ ..... VI
,..... ... en c
oJ ... VI... .... ~ oJ ...
- •
...'"a. -...c
...0 < "
~.
•.&:
..."" .,. 0
0
.&:... 0
~ VI
<.!)
za:: ..... O~
0« c.. l.U
.&:
... "" en 0 c ,.. C
, a. VI
.&:
'"
... v ......, ..
eo;; >.. ... ....
,.. ... ...... "" .D " '0C c: ...
c o... ...
VI ... I
o
• ... '" v " ... ... ... ... lD
<'l C
.;;;o~
Ca:: o <l.l
Ec.. Vl 5
'">
ures 10 through 13 are entailograms showing both the implicational and contrast relationships among the beliefframes from the east Florida sample6.
Cluster I (Fig. 10) contains belief-frames that are mostly negative in character. The following are two examples of how to interpret the diagram. The ordered relationship "only eaten by certain classes of people" entails that the fish is a "scavenger," which in turn entails that it "must be skinned." Many infonnants disparagingly described certain scavenger fish as being only eaten by certain classes of people. In addition, many of the scavengers were seen as requiring skinning (e.g., sea catfish) .
A second example is the string "can only be cooked one or two ways" which entails that they "do not freeze well" (don't keep well in the freezer), which in turn entails that the "meat is oilytasting." In contrast, for example, cluster II (Fig. II) shows the relationship among positive characteristics with respect to freezing. Here the string "meat white when cooked" entails that the meat is "white when raw" which in turn entails that it will "freeze well."
Figure 13 shows examples of contrast relationships. Lines with cross-hatching denote these relationships. Contrast relationships are shown outside the clusters discussed above for the sake of simplicity and readability, but they could have just as well been included. An interesting example of such a relationship centers around the attribute "easy to clean." If a fish is perceived as "easy to clean," it will not be "poisonous," "ugly," or "slimy."
The importance of both the item-byuse and entailment analyses lies in their ability to infonn and guide us in our attempts to change angler attitudes towards the less traditional sport fishes. These analyses, for example, tell us that fishermen routinely attribute negative culinary characteristics to fish they have never tried. It is much easier to change attitudes in situations where there is some degree
6Data from the east Florida item-by-use was dichotimized using the following break point: Alpha> 3. The entailogram was produced with the aid of a multidimensional Guttman scaling program written by Doug White at the University of California, Irvine. Relationships shown are with no exceptions.
49(2), 1987 /29
c .....
NON-SPORT"" Atlantic Needlefi~h
Spadefis • Gray Triggerfi~h •
Gag·o • Queen Trig'} - ladyfishJewf i sho o Silver
• Gaff topsail CatBighead Robi"
o Scamp Sea Catfish
eo Ra inbow Runner- Tripletail • Northern Sea
-Sma Tautog O
o lane Snapper
Gray Snapper 00 Hutton Snapper \larsew Grouper OQ ptasau Grouper Blue
eO uroupe~- ~ed Snapper o Northern KingfishBI ad l>l'oupe r
·Pinfish o Red Porgy Black Sea Bass 0 0 Schoolmaster Snapper liahoo
I 0 Tarpon ODolphin 0
terfish 0 0Cobia - Amber jack 9 f i ~ h • Be a c h \ltd t • l itt Ie Tuna
O~outhern Kingfi~hite Perch • •Silver Perch
Sheep~head-
Southern
POOR EATING
Spiny Dogfish
usky Shark •• lemo~ Shark Sa ndba r Sha rk
Smooth Dogf ish
• Stingray
_ Barracuda
GOOD EATING
SPORT
Figure 4.-Multidimensional scaling for North Carolina: Dimension 1 vs. Dimension 2. Dots indicate underutilized species and circles represent utilized or preferred species.
~ .... 5' t'Il
"t'J<::;. ;: t'Il ....;;;. '" ~ t'Il ~;;;. ~
~ \0 ~ '- AtlantIC Spadefish....... • • TripletailGrunts. Gray Triygerfish ~ GaaO 0 ·Ouren •
')camp'-J Triggerfish Spot. Pin fish
Smooth Puffere .0Si Iver Jenn~ Mutton Snapper Blact Grouper • .Pigfi sh • • If llet o 0 Red Snapper
Northern Sea Robi~ • d f' h SlIver erch Gray Snapper 0 Red G,'2>,,~er 0• [a y IS ()JewfishSheepShea~each \lId t i ng Bighead Robin • BlueoRunner
0.( roater\lhlte Perch. Rainbow Runner 0
• S~uthern Kingfish 0 Schoolmaster SnalJperSea Catfish
Northern Kingfish
NOT PREFERRED Bluefisht eGafftopsail (at Snook PREFERRED o 0 0 C b'
lIeakfish 0 la
e Red Drum("evalle Jack O
Southern Flounder oDolphino ~Klng Mackerel
Striped BasSO lIahoo oO-Sfanish Mackerel o 0 a d T oul
Smooth Dog fish. Amberjack Tarpon Spotted ~rou • 0 0 PompanoSUfTlner F~ounder
Sixyill Shark. • e Stingray Jla rr acuda
0" 11 Shuk.
Grrdt Wli i te Shark•• Mako
•Blaclctip Shark
Figure 5.-Multidimensional scaling for Texas: Dimension I vs. Dimension 2. Dots indicate underutilized species and circles represent utilized or preferred species .
....... l..N .......
I I I !.01 ittl .0
"'I "'I '" "'I '" U " ~ ... I '-'W
! :;; I 2 !I
:~;' ~: ~i ~ -I, I~ .~~~ ~~ li~~Ji e I ~~~II~
<ll ! .... U);S ~'"' I ~ ~O\ ., ~~ 0 ~6~ .c x \..l Ql :J a> >. c ..c ttl C :J c..c '0 til - \.I..ll [''01 '"
xro~ I~E~s~,~~c~~ I~&~j :: ~.c~ l:~ ~~~~ ~ &3~£~~~ 'I ~ ~ 'g ~ ~ ~ ~ ce 0 (J}13':..c; - 0.. ~~ :J ~I \..J .c..c:..c. ~ o...~ E I~ ~ C" ~ c .c. ~ \..J C" i5 ~ '0 8~.c l~ ~0'1 C "0
"r-'\ V U ..... ') clro u ~ ..... 0::: \..J (' \..J .c. \..II \..l 0 '"'I (l) til til ttl til Q> \..l 4-l E-< : C C Ql til Q) Q) ..... til '0 <1.1 Ql, Q) Q) E-< til I· .... ~ ... \..J ttl 4-l..w 0 U x..x.x l ro 0:: Q) .w ~ Q) .D Q) x ,j.) .............-4 ,....j Q) Q) ~x ..... ttl 0.. 0.. 0.. ttI.c. .x .... c 0.. ~x 0'10.. (l) ..... O'I.L.l <1.l Ql)..lX >,_..-1 0.. ....... \..l \..J \..J11l>.w \l....I 0 C '> C"'lttI.w C\l....I\I..I"'-l o..E '>'0'0 E VoW 0.. Ql o..o.'..-l a.CI.L.l:J:J U Ol·..-l,.. C 01'" "'~ .c\..JU'OC\..Jro-rorottl:J .... rol.L.l~· ........... ·.... ..wOO:JOlC~· .... \..J-roCroro ..... EOQ)roro.o-O'Ooororo· .... \..JQ>· ro.c:JC~:~j~~I~~~~~~~~~(J}~I~:~~~~~~~~~~~~~~§g~~~~88~&~~~~~~~~~~~~~
o 1 2 17 19 6 43 17 8 7J 2} ~ 5 16 34 J;l 40 41 54 55 56 10 32 15 2.3 24 18 52 22 24 Jl 51 53 3 49 25 45 )) )3 J5 9 II 36 50 13 14 34 12 44 J1 46 47 42 48 4;:n 21 Mt')st pe'1[Jle 8at 13000101° 1 000 I 0000 010 01421205621) 4 511 10131412141212131212 l516 17 8 810 9 812 a 91312
I prefer t-, catch )) 4 2 2 ) a 0 1 1 1 0 1 0 1 1 2 0 0 0 0 1 1 1 1 1 3 S ) 1 4 1 2 6 S 710 710 911 10 910 91611 S S ) 4 3 q 8 610 2 Ea'5y t·, clean 11 4 3 3 3 3 313 3 ) 3 3 3 ) 4 ) 1 21 3 ) 3 ) 4 S ) 3 5 6 4 4 ) S 4 510 910 4 6 610 10 10 9 a 12 10 5 2 6 9 811 91011 7
Can get big thick fillets 0r '5t~aks 36 4 1 I) 0 20004 4 40000000000 1 0007 20000 200 1 4 1 S 711 5 5 8 311 8 2 0 1 III 7 114 1
~~~~t f ~~~~C~~ ~ t:~ ~ ~ i ~ ~ ~ 1~1 ~ ~ ~ ~ ~ bgggggl ggg6b ~ g6~ ~ ~ ~ ggi ; ~ iii ~ ~ ; ~ l~ ~ ~ ~ ~ ~ ~ ~ g ~ iIi i ~ ~ Easy t'1 ca tch 6 10 7 8 7 a 11 a 6 5 7 3 4 4 4 5 4 51 3 3 3 S 7 10 6 10 2 5 2 ') ) ) 3 13 a 4 9 2 5 ) 4 ) ) 4 5 5 4 8 6 3 ) ) 6 3 10 6 6
NQt sturdy, durable, q!.Y'ils -3asily 14 3 ) ) 3 ) 3 3 3666 3 ) 3 334 3 3 ) 4 3 ) 4 ) 3 ) 3 3 3 ) 3 3 4 39 3 4 4 4 4 3 3 3 3 4 3 3 ) 9 8 4 38 S 4 MU'5t cut 0ut red <:>teeaks fr ...,rn meat 49 5 4 2 2 4 21 2 2 2 2 2 ) 2 2 2 2 21 2 2 2 2 2 2 2 2 2 2 2 :2 2 2 2 2 2 2 3 2 2 2 3 7 ) 5 2 3 2 4 ? 4 2 2 7 5 13 a 2
F~eeze ....e 11 16 4 ) ) 3 ) ) ) ) 4 ) ) 3 3 ) ) 3 3 3 ) ) 3 3 ) ) 3 3 4 3 3 3 3 3 4 5 4 6 4 7 6 a 6 5 6 7 10 8 3 5 3 4 4 S 4 ) 4 4
Can C'10k a~~'5~a~" y;~ei~~: ;~ ; iii i iJ iii i i ~ ~ ~ ~ i il i ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ j i ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 1~ : ~ ; ~ ~ ~ ~ : j ~ ~ "Ea;ot"'ec;n-::;Owh"'e;-;n;-C~+lgO't~'-'·''';:~~0~;e'C:".~",:+~+~ ~ 6 ~ ~ 6 ~ ~I ~ ~ }i---f ~ ~ ~ gg ~) ggg ~ ~ i i ~ i ~ ; 1 i ~ b~ i }-~ ~ ~ ~ iIi ~ ~ i : i ~ ~ ~ i-+-~-H-~
Can nevee get big t~~~kh~~~l~~~h~~n~t~~~~ ~ 6 ~ g ~ g ?I ~ ~ g ~ g ; ~ : ~ ~ ~I ~ ~ i ; ; ~ : ~ g ~ 6 i j i 6i : ~ ~ i ; ~ ~ ~ i ? ~ i ~ j ~ g ~ ~ ~ i i ~ ~ rnesn't even ~~:~c b~ i~~ i~~:~ ~ ; ~ i ~ ~ ~l t i : ; ~ t ~ ~ ~ ~ ~I ~ ~ i ~ ~ i ~ i i ~ ~ iii i ; ~ ~ i ~ i : : ~ i ~ j i ~ i i t i ~ i ~ 7 ; i
Stu~1y, dueable: d(,esn'tv:~~iie~u~~~~ jj ~ ~ ~ 6 i ~I i ~ i ~ ~ t t ~ ~ ~ il ~ ~ t t t ~ ~ ~ i ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ j : j ~ ~ : : ~ ~ ~ ~ ~ ; ~ ~ ; ~ ~ Meat '"las mi1.1 taste 18 0 1 0 0 0 010 0 0 0 oTO' 0 1 0 ~I 0 0 0 0 1 1 0 1 0 2 0 1 00 1 6 ) 8 7 2 5 4 7 5 6 2 96-7-i-S 0 4 3 0 1 00 1 Meat teKtuec tend~r 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 2 2 0 0 1 2 0 2 0 1 1 2 5 6 9 2 5 3 ) 7 5 511 2 4 1 2 0 8 6 5 5 1 I 0
Meat ....hite .... hen c<10ked J5 1 0 I 0 1 010 0 0 0 0 0 0 0 0 0 010 0 0 1 2 0 1 0 1 2 0 0 0 1 0 <1 4 4 6 3 S 2 7 5 5 1 9 5 5 0 2 0 ) 2 1 2 1 2 0
Mp.atN~~~t~l:~~n1l~:~ ~ ~ ~ ~ ~ ~ 61 ~ ~ ~ ~ ~ gg? ~ g ~I ggg ~ ~ ~ ~ ? ~ ~ ~ ~ g g~; ; ; i J j ~ ~ : ~ ~1~ ~ : g ~ ~ ~ ~ 6 j g6 ? Most ~e0ple 'in n-)t eat 2 aI41S1314L5141211-fT12TI-u 11 101014 6 95 5 6~12 S 6 7 6 6 4 4 t 2 Ill) 2 2T2:rrt-i14-02""124~
I have neve~ trie<1 eating 4 4 a 912 910[10 9 8 8 II 711 11 11 10 Hill 11 a 5 S 4 S 7 7 7 6 7 6 4 6 1 0 0 0 1 1 1 2 2 1 1 0 1 1 2 2 2 2 1 0 ) 1 1 0 Edible, but the~e ace ~ette~ fish to keep 62 10 6 4 4 8 2 912 5 6 5 5 1 ) 7 7 4 a 0 1 4 ) 4 5 6 4 1 2 4 2 1 0 1 0 1 0 2 1 1 I 0 0 1 1 1 1 1 ) 0 0 0 0 0 0 1 2
Dange~~~~e~'~~~a~1~~ ~ g ~ ?gg ?Ig ~i 1; l~ 1; ~ ~ i i ~ 1~1 ggg ~ gig ~ ~ 6g ggggig g g ~ g g ~ g 6 g ~ g g ~ g g gg g ~ ~ i ~ Only eaten by ce~tain classes "f pe',ple 59 1 ) 0 1 2 019 0 ) ) ) 0 0 0 2 2 1\ 0 a 0 1 1 1 1 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 3
Ha~d t<1 clean 10 0 1 0 0 0 0 4 ') 1 1 1 0 0 2 4 4 2 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 1 1 0 D 6 3 2 0 0 0 0 3 0 2 2 8 0 0 0 0 0 0 0 )
N-1t ~~;~~ ~:~~u~:C~~~:0~~~; ~ ~ 16 ~ gggl i ~ ~ 6 6 g ~ : ~ ~ ~I gggggg ~ gggg ggggggg gg g g6 ggg g gg6g gg g g g ~ ~ 6 Sma 11 ~~~~ ~ ~ 6~ 1; ~ il ; ; ~ ~ ~ ~ g66661ggg1 ~ ~ ~ i ~ gbig gg ~ f g~ ~ TIT~Tg r~ 6i 0 ~ ~ n1-r-r~
Slirny fish 5S 0 1 0 4 1 2[ 2 S 0 0 0 0 0 0 I 0 110 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 2 0 1 0 0 1 0 1 0 0 ) ) G00d pan f i '5h .34 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 ) 5 4 2 4 0 0 0 5 1 0 0 2 2 4 0 1 2 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 4
T<,·) ~;:~ 1~'~t~~t~~~ ~~~~ ~ 6gg ~ ~ gl ~ g ~ ; b ~ ~ 1b ~ ;1 ~ ~ ~ ; ~ ~ : ~~ ggg ~ ~ g ~ ~ ; g6g66ggggg ~ gggg ~ gbg? g ~ 'teat 1n ~~~<1q~';t c:~~: i ~ 6gci ~ 16166gg g g 6666 ~I 6g g??g 6 g ~ 6 ~ ? ~ ~ 0 g ~ ~ ~ 6 g g ~ ~ gg ~ ~ ggg ~ ~ ~ ~ ~ ; ~ ~
Eatc"l .... hen sna 11, f\0t hig 7 4 S 1 6 1 0\ 1 1 3 2 0 1 0 0 a 0 21 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 1 0 0 1 1 0 0 0 2 0 anI 1 7 0 0 1 1 0 0 6 3 0 Often have -'''0~rns ')~ paeasit~'5 56 9 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 laO 1 0 0 0 0 1 0 2 0 0 0 0 1 0 ) 0 ) 0 7 0 0 1 1 0 0 0 0 0
________________~~_~_~aJ:~_~,~~_~i ::~_~:~ ~ ~ ~ ggggl g ggg ggg g ~ ggl ~ ~ ggg gg ~ gggg g g g~ gg g ggg6 g ggg66g g g g g ~ i ~ ~ l~ Must ~~ q"aked bef0ee C0·1king 17 1 0 1 0 31ifO-~ -O-O--oooarO 0 0 0 0 0 0 0 0 o""""1f"OOo 0 2 0 0 0 0 0 0 1 1 n 0 1 0 1 0 0 0 0 0 0 1 3 2 0
Big brlnes 31 1 0 1 1 0 0 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 ) 1 1 1 0 0 1 2 3 1 2 0 1 Q 0 0 0 0 5 1 Medt te>ttuee c-)a~se ...,~ ]rai"lY 42 2 I I 0 1 010 0 ) 3 2 0 0 0 1 0 010 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 ') 0 0 4 0 4 5 4 4 0 0 8 0 1 0 0 0 0 0 0 1 2 0
Meat -,n the hari ';; ide 45 2 0 0 0 I 0 1 1 6 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 3 1 1 1 0 0 1 0 0 0 0 I) 0 0 Ta'ite'5 1 ike i-,d inc 23 0 0 0 0 0 01 0 0 2 1 1 0 0 0 0 0 01 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1
Ileat is ste i"lgy ·11:' t0u1h 47 3 0 0 0 0 0 0 0 ) 1 1 0 0 0 0 0 4 0 0 (II 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 Has muddy t~ste :;:e 0 0 0 0 0 01 ') 3 1 1 1 0 0 0 0 0 01 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 0 0 0 I 1 2 5
_~ ~~.'!.Y_~!'I~~ __~U.!..~ ..'L...=!!?2.~_~~!.._t_~.£~ 60 0 1 0 0 0 1 2 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0 1 0 I 0 0 0 0 0 I 0 1 0 0 0 0 0 0 0 0, 0 2 0
111ea~~:s n~\~~~~~e s~~ U ~ i ~ ci 6 ~ 6 ~ ~ ~ ~ ~ 66 ~ 66 ?I 6666 ~ 66666666 ~ 6 ~ i ~ 6 i 66 ci 666 ~ 66 i ~ 6 0 f i ~ ; 1 ~ Can on ly C')0~'e·~~e t~.~t~;'\~:~; ~ i ~ ~ ~ ggl gg ~ ~ ~ ~ gggggl ggg ~ g?gg?6 6gg gg ~ ~ 6 ~ ?6 g 6 ~ g g ~ ~ ~ ~ 6 gg g ~ ~ ~ ~ ;
Me~;a~t~.~~~ ~::~t~g ~ ~ i ~ 6 J ~I gg ~ g6 i gg ~ ~ gl g g gggggg6 g ~ g ~ ggg ~ ~ gg g g ggg ~ ggg g g g g g i i it 19 ; Meat dark .... Ilen ra,* 2S 5 2 4 1 13 11 1 1 0 0 0 2 0 0 0 0 01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 D 0 0 1 0 1 0 1 1 1 0 0 0 0 0 0 2 IllS 1
BI.ndy meat :B 2 1 ) III 1 J 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 I) 1 1 9 2 1
Figure 6.-East Florida sorted item-by-use matrix based on row-row and column-column similarities.
Marine Fisheries Review 132
la
Can get
o tlr'>st genple c~t 1
ij·)tt")m feedec-, 61 Easy t'? clean 11
E1Isy t,) prer>are 41 free ze we 1 1 16
'''Ieat .... h [te ..... hen ct)t)ked 26 Heat haS' mi 1<1 taste 18
Cafl c,,<")k any way y')u 1 i ke ]7 I prefer t,) catch 3
big thick. fi llets .)[" steaks 3S fI1eat t~'I(tLJre f ir<n 43
StLJr1y, durab~:~e~,);:~~tb~~i~t)~LJ~::t~ l~ ~ ~ ~ ~ ~ ~ ~ ggggg ~ gggggg ~ g?l gg; ; ~ ~ ~ ~ ; ~ ~ ~ ; ~ ; ; ~ ~ ~ ; ~ j ~ b ~ ~ ~ t ~ ~ ~ ~ ~ ~ Ib ~lea\~~~t~l:~~nm~:~ ~ ~ ~ b gi ~ ~ ~ ~ ~ g~ g~ gg~; ~ gg~\g g~ j i; ~ i;:; j;; ~ ~; ~ g;~ ~lr ~ ~ ~ g; ~ ~ t ~: ~
~leat t~:;~r~,) t~~~~~ ~ ~ ~ ~ ; ~ ~ ~ ~ g ~ ~ ~ 19 ~ ~ ~ ~ 77~-t4-H+~ i ~ ~ ; i 6i ~ ; ~ ~ ; ~ ; 1; ~ l~ 1~ ~ ~ i i g i ~ ~ ~~+i ~~: t f ~~~ ~;~J Ei~~~ i~ Ij 1~ ~ ~ i ~ ~ i i ~ ~ ~ ~ i i ~ ~ ~ ~ ~ i il l ~ iii i ~ ~ j ~ ~ iii i i j l~ ; ~ i ~ i ; ~ ? i ~ iii ~ i ~
'''Ieat dark wh~'1 ra .... 25 7 12 1 1 2 2 2 1 2 3 5 2 1 1 2 1 3 I 1 I 1 11 1 1 1 J 1 1 3 2 4 1 1 1 I I 2 3 2 5 2 1 1 1 2 3 2 1 1 1 1 1 1 1 1 2 'l'lt stur'iy, durable, sp0i15 easily 14 3 2 1 1 44 222 1 1 1 1 1 1 1 1 1 1 1 I I 1 1 2 J 6 4 1 2 2 142 1 1 22 146 2 3 8 2 4 1 1 22 1 1 3 1 I 1
mes n~~r~r~~~e~~~~ ~ ~ ~ ~ ~ i ; ~ 66 ~ 6 ~ ~ ~ ~ ~ ~ 6 ~ ~ 6 ~16 ~ 6 1 ~ ~ j ~ i i 6 i j ~ ~ : 6 i ~ ~ ; i ~ 66 ~ 666 6 ~ ~ ~ : Can never Jdt big t~.~~l{h~~~ l~~~h~~n;t~~~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i : i ~ ~ ~ g ~ ~ ~ ;1 g g ~ ~ ~ g 666 ~ g ~ ~ ~ ~ 6 ~ ~ 16 ~ ; ~ 66 ~ ; 6 ; ~ i ~ j :
MLlst he s'1aked h~fore cooking 17 2 4 2 2 6 ') ') 3 1 1 2 1 1 1 2 1 1 1 1 1 1 II I 1 I 1 1 1 I 1 2 I 1 1 1 1 I 2 1 2 2 1 1 I I 1 I 2 I I 1 I 1 1 1 1 Only Qaten by certaif\ clas~es 'lE r>e'lple '5B 2 J '5 6 4 4 4 2 3 3 4 ) 4 1 2 3 I 3 2 1 1 I 1 1 1 ) 1 III 1 I 1 1 1 1 1 ) 2 t I 2 1 1 I 3 I 1 1 I I I I 1 2 L
Ta~t~s_like i-1~ ~ ~ ~ i ~ ~ ~ : i ; ~ ~ 16 j ~ i ~ ~ ~ iii j j i i ~ ; ~ iii i ; j ~ ~ ~ ~ 2~1 i 1 il ~ j i ; : iii 2i--3~ ',',-,--,-,:,;,------------~t pe'lple .10 r'\'1t ~at 210114 11 21115 1 i515lOT~-IT-i1i---r-TT5 ~12 2100. 0 ~o-Ori---j----i-a-02 000 I) 100 I .,.A
I have never tried e:ltl'1') 4 5 810 10 11 712121210 15 12 13 1310 71) lIto 13 9 6 7 7 2 2 1 1 1 1 0 2 0 1 0 0 0 1 0 0 0 0 0 0 0 4 6 J 3 4 6 5 4 4 5 6
~·hble. tn.t there Me ~:~~:~'1~~s~'1t'~a~~~~ ~ ~ ~ i~ ~~ ~ ~ ~ ~ i ~ ~ ~ i ~ ~ i ~ ~ i ~ ; ~1 b ~ ~ ~ b gggggg ~ ~ gg6 i ~ ~ ; b g ~ i ~ ; ~ ~ g ~ g ~ ~ ~ scav~~1~; ~ ~:~ ~ ~ ~ I; l~ ~ ~ ~ ; ~ ~ b ~ i ~ ~ 6 ~ bbg ~ gl gggg ~ gig t ~ gggggig ~ ~ i g ~ ~ ~ g ~ ggggg i ~ t
Thc':) .... back because ugly ')7 t 1 0 8 0 0 1 2 0 1 1 0 010 910 '3 1 S 2 0 310 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 1 1 a 0 0 1 0 1 0 a 0 0 0 0 0 0 (1 0 1'1L.st be .,kinned 12 1 0 4 7 '5 6 5 1 0 0 0 0 0 0 0 2 0 0 1 0 0 '3 0 0 0 I 0 0 I 3 0 6 0 1 0 0 0 0 3 0 0 0 I t I 0 0 1 0 0 0 0 0 0 0 0
-----------''1~at is ~~r~~~~ ,~': ~~~~~ 4j ~ g gg ~ ~ g ~ ~ gg gggg g6 gggg 61 g 6 ~ ~ g g : 6 gI~ i ~ ~ ~ ~ ? ~ 6 g ~ ; gig ~ i ~ ~ gig ~ ~ g ~~~~n~;t:~e~e~:~~: ~~{:.)~.;~: ~ g ~ g g 6 g gIg ~ g g g g ~ 6 ~ g g ~ g g gl g g g g g g6 g g ~ g ~ ~ 66 g g ~ ? ~ ~ g ~ g g g g g g g g ~ ~ ~
Sc<lven~er~, but ricky ab()u~'l~h~~d~~e~a:~~ ~ g g ~ ~ 666g ~ g g g g g g ~ g g ~ g g gl g g g g gg g g ~ g g g g g g g ~ g g ~ g g g ? g g g g g g g ~ gg Edten when smallBi~·)~~~~ Ji J~ 6 ~ ~ J ~ ~ ~ g 6 ~ ~ 66666g 6ggig g ~ g 6g ~ ~ ~ ~ g g g g g j ~ ~ 6g 66 ~ 66; g 66 g 6g 6 g
Often '1ave ....')rms 'lr paras i t<:!'; 56 5 0 I l 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01 v 0 a 0 0 0 0 0 4 0 0 0 0 0 012 0 0 0 0 0 1 I 0 0 2 0 0 0 0 0 0 a 0
-------'M"'e"a"'t-''1as a H:~~,,~.~ ~;:~~ ~ ~ ~ ~*f_i44+t+-6-~+-~~-~ ggg~ ggggggggig ggg-g-gr4-1gg~+%-H+~-g-g ~-%-f--g ~+~ Medt texture c',arse 'lr grainy 42 2 1 0 0 J 3 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 g: 0 0 0 1 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 I 0 0 0 0 0 0 0 0 0 0
Meat '1n th~m:~~d ~~~: ~ b g-¥-+-~-6-8t-%-%+-~ g ~ g g g g g g g ~ g g g ~ 6; ~ ~ g g g g g g g g ~ ~ 6b? ~-H~-& g 6g ~~4 %- ~ ~ Go'1d pa'1 ~ i"h 34 0 0 0 0 1 1 I 0 0 0 0 0 4 0 0 0 0 0 0 1 1 01 0 0 1 2 2 1 0 I 0 0 1 0 2 0 0 0 1 I 0 a 2 4 0 I 0 0 0 0 1 0 1 1 5 3
'1eat '1n the s'1ft side 46 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 I 6 6 0 1 0 0 0 0 0 0 1 1 0 0 '3 0 410 1 0 0 0 0 0 0 0 2 0 0 0 r0'1 ~mall t'1 bo)ther .... ith 51 0 0 1 0 2 1 1 0 0 5 1 212 2 0 1 0 0 1 J 4 110 0 3 J 0 I 1 0 0 0 1 0 1 2 1 1 0 0 0 1 2 0 1 0 0 1 1 0 0 I 1 4 7 7
Used m<)stly f'1r bait 54 0 J 0 0 0 0 0 0 0 0 1 316 0 0 0 0 1 0 6 2 0 1 1 0 1 g~ ~ ~ ~ ggg? ~ ~ g~ _~ ~ ~ ~ ? g ~ ?g??g ? g~+_~
Can 'lnly C')'1~e,~~~'1,~~Y t~~S~~~~ ~ ~ ; ~ ~ ~ ~ ~ ~ gg~ g~ ~ ~ ~ g~ 0 gg gl gg~ g I 0 I 4 0 0 2 0 I 2 1 2 1 6 6 4 I 1 0 2 1 0 I 0 0 0 0 0 0 0 "lust cut ';ut red streak fC"'lm meat 49 5 3 1 1 2 2 2 0 0 1 0 0 0 0 1 0 0 0 0 0 0 010 0 0 0 0 0 2 2 3 I 0 0 0 0 0 2 0 6 8 I 0 0 0 3 0 0 0 0 0 0 0 0 0 0
Meat stc',ng tastir'\g 22 4 ) 0 0 0 0 0 J 0 0 2 0 0 0 0 0 000 0 0 0000000000 1 1 100002 1 54 3000 J 0 0 1000000 1 Bl'10dy meat Cl 2 12 tOO 0 0 t 1 2 4 0 0 0 0 0 0 0 0 0 0 01 0 0 0 0 0 0 1 I I 0 I 0 0 0 0 2 1 2 2 1 0 1 0 2 () 0 1 0 0 0 I 0 0 0
Are best sm-)ked )9 10 1 0 0 0 0 0 1 0 0 I 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 4 6 15 0 0 0 0 1 0 0 0 0 0 0 0 0 0 Can be eaten ·)nly if s:Tl'1ked 40 6 1 0 0 0 J J 2 ,) 0 1 0 0 0 0 0 0 0 0 0 0 010 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 a 1 1 4 0 0 0 0 0 0 0 J J v v 0 0 0
Figure 7.-West Florida sorted item-by-use matrix based on row-row and column-column similarities.
49(2), J987 J33
I I I I
~ .0,
'" U 0U]
~
~ 'r'
'" " :r: ~" S .~ I..J
.J:: ttl r 0 IJ' Q> g ~
x to
~-g
~ t
~ i ~!
~ ~ L.'
-?.J::Q)! .c .c --;;; ~.~ ~ I~ .~.~~:;~~;j~
~ ~ Q)
~-g ~~; ; ~ !i;:;7~ \.:t! ~ c E5:: ~tt>-o=-:
.~I .co>
g ~ fl ~~?
;I..J 'Q) --'
)g~~.c~
1 ~ ~~: I ~ ~.~
~II ~ .... ~ :::!, ~ ~ Ul ~ ~ ::
>oc tl~g' t~ e: ~ ~ :5 .c ~: ~ ttl I..J Cl: ttl
~~:~~.~l~:c::1..J ~~~~c:
~ -g-S c:: 0
~ ~ ~ ~ 3 g:
> (f)
6.c~ :: tOtO ..... tV
.c£~Sic~ ';:'~ ~.8~~0:0-S&;5~.;.;~~;:lOx ~~I~ ~locS': ~~~.v o.~~.b ~~~lx·5 ~.~~~ ~-g:<::~ g, 8.g,g('.~ ~ g,~.>g ~
a. ... .., 'C X V!.- C' : C : Q:' 0.. >. ........ "? E E :> c U ttl: U C. c ttl te 0.. c.. t:' Co.w C!l(1) I..J ...... I..J I..J 1..""" _ '-' ::"\ ;:J .w .w .w .., Q) :; ~ ~ ;J U-J .w .J::: I..J I..J c·.... Cl ::J .......... C' "': ttl 0' r::' ttl· .... ":; '- . .0 ." ..... 0' C ;J .... 'C' :t ro I..J C ttl '0 ......... oW ttl _: ttl .... E In r: c C' ;:J ': c._ C C ttl ttl.r::: -::: .... rt· ... "'.J 0
~ ~ ~ ~ 0 ~ ~ ~ (f. (,~~:S; S~~~~ ~:3;; ;-:'O::i"n: i; t:~,:;; (.9)£:;' bl ~V; ~~;;; ~l;;;~ g ~i;:; g-a;~ ;':8 ~ ~ 03. (.~:!i &§ (.~~ g~ o 1 24) 6 16 6.2 17 61 a 40 J6 7 ~ n 13 41 :B Xl 9 1244 2J 21 24 552 I'J 10 :it 22 J6 53 '59 54 55 56 63 60 349 25 42 45 1O 32 4 13 20 II J1 15 14 34 35 o(l so ]5 3347 57 XI
M')st ;>e')plc cat I 0 0 1 1 a 0 0 a 0 0 0 1 1 a a a a () ') 3 4 31 5 1 a a a 1 0 1 2 a a 0 a 1 2 410 IJ 12 16 14 16 IJ 13 10 15 1I 12 12 IJ 12 10 8 6 B a II 7 9 I prefec t·) catt'''' ) 3 laO 0 a 0 a a 0 a a 0 0 a 0 I 0 5 2 1 0" 1 0 0 a 0 a 0 0 I () a a 1 0 a I ) ) 711 IJ 4 4 91212 7 6 5 ') 5 4 8 8 \ ) ') I 0
Easy t) clean 11 a a 0 0 a 0 0 0 a a a a a a a a a a a a 0 III 1 a a a 0 0 0 a 0 a a I 0 a a 4 1 612 6 7 7 910 12 ) ! 1 3 2 ) '] a 2 2 I) 2 I N1t ~t\,.ody, durable, s:}')i 1<; easi ly 14 ) ) '] '] ] ) '] J 3 ) 3 ) 1 ) 3 '] ) J '] 3 ) ) 4 ) 3 ) '] ) 3 ) '] 3 ) ) '] '] ) 3 5 ) 1 4 ') 3 .1\ 11 '] ') 4 ) 4 '] ) ) ) ) ) ) ') '] ']
freeze ',Ie \1 16 2 2 2 2 2 2 2 2 2 2 2 ~ 2 2 2 2 J 2 J. 2 2 21 ) 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 ) 4 ) 5 7 7 ) 12 6 6 '] 3 4 4 4 ) '] .3 ) 4 4 2 'teat ....h i te ....hen co)<)k~tj 7.6 2 2 2 2 2 J. 2 2 2 1 2 2 4 2 2 2 '] 1 2 2 3 .3 '] 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 ') 4 7 IS ') 411 7 5 ) 4 4 '] 4 ) 2 4 4 ') ']
Can (,.,·)k any '<lay Y0U 1 i I(e nil I IlL 1 I I 1 1 I 2 I l I 2 1 1 I I 21 2 2 1 I 1 I I 1 I I I I I I 1 1 4 2 5 7 7 4 ') l3 12 8 5 6 1 4 6 a "} ) ) 4 ) 4 Easy t 1 pcepMe 41 I 1 I I I 1 I 1 I 1 1 1 1 1 I 1 1 I I I 2 I I 2 1 1 I I I 1 1 I III I 1 ) 2 2 a 6 4 6 6 9 a ) ) 2 2 I 2 4 1 ? I I 2
'leat has mi 1.1 taste IB 0 a 0 0 0 a a 0 a a a 0 0 I I 0 2 I 1 0 1 ')10 0 l 0 0 0 0 a a 0 a a 1 0 0 '] 4 ') 2 ) 1 2 r) 13 ) 4 2 0 2 ) 1 '] 0 I 0 I 't~at .... h i te .... h~n ra .... 24 0 a 0 0 a I 0 a 0 0 I 0 ) 1 l t 2 1 1 0 2 a 0 a a 0 0 0 a 0 a 0 0 I 0 ') a ] 2 ') 2 4 ') 2 013 4 ') 3 0 1 I '1 2 I 1;) I
Nkoa fldky 'neat 46 a 0 0 0 0 0 a 0 0 a 0 a 0 a ° 0 a 0 1 a I 01 a 1 () a 0 a 1 a a 0 a a a a 0 () ] 1 1 a 4 2 1 I 7 2 2 ') a 2 4 2 1 () 2 1 ')
______ ~ Md'lt t~:~~rTlt~~~7-~ 4: g*g gggg~+_~ ~ ~ ~ ~ 0 0 0 I 0 1 ! 0 0 0 1 gg~ gg~ gog ~-i+H-ci-&~4 '] 1 I ~i-H-~+--H--H e;.,)<1 pa1 f i-;h 34 0 a 0 0 0 0 0 0 0 0 0 0 1 a a t'J a I ggg ~I 2 ~ 6 g gg 1 a a a a a a 1 a 2 IJ 7 2 2 915 ) 5 a a 0 0 0 a a a 0 5 I) 1 a 0
Fhtt)'11 feeders 620 a a 0 2 a 0 0 J 2 ) 4) 2 2 6 1216] 312 4 a a a 2 I () 1 0000 0') ') ') 0 210 7 I 5') () 0 1 6 2 204) 2 2 2 i Eaten when bi'], n,t small 8 a a 0 a a 0 0 0 a 0 a a a 0 001 0 a :) 0 I :2 4 0 0 0 0 0 a 0 0 a 0 0 021 1 a I 46 a 7 0 a 0 I 00 f) a f) 2 a I !) r)
Can rtever ~~t Olg t~~~\~~~1~~~h~~n;t~~~~ ~ r g g g ~ ~ g g ~ ~ ~ ~ t g ~ t g : g g ~ ~I ~ ; g t ~ g 6 g g g g g ~ 1 g ~ iii ~ ~ : ~ ~ gg g g ~ ~ ~ ~ ~ ~ i ~ ~ ~ R'Jny 30 0 1 ] 0 0 a I 0 0 1 I 0 a 1 I I 1 I 0 a 0 21 I 10 1 0 ) 2 1 I 0 a 0 I a 0 0 2 2 1 I n 2 4 I) 1 I a I 0 0 1 1 0 0 4 I f) a t
-roo SM~ 11 t) ~~~~~/,~l~~~ ~ ~ 6 ~ 66~ 6 ~ 6~ 0 666666 ~ ~ 6g ~I ~ 1~ ~ 6 i 6~ ~ 666~ ~ ~ ~ g ~ b~ 6 ~ ~ ~ ~ ~ ggg ~ ggggg ~ ggg ~ --------------~t~)"[)Te-a;~t ·'!at 214 IJ 7 71011 12 8 6 712 5 -li'""m 10 I ' \I I:> ] 6: 5 S6B~)-y-rTl~2 0 1J"'O""0'()o-o""i.JlJOl o..,--rOO-o-j-'-I-r1j"""'7f"Q
I have never tciel"l e1ti:"l') 41214101OlJI2101313I011tl SHUll 777') ') 5114\0121210810 9WlO1211 775 II I 1 '10 l. 0 a a 2 <I () I 0 I S 1 2 2 4 1:2 N·)t eaten becal.<;c ~ lis)n')~<; 20 a a a :) 0 0 0 a 0 J 0 0 () 0 0 0 0 :) a a I 0 0 a 0 0 0 0 0 0 0 a 0 0 0 0 0 0 a 0 0 a 0 0 0 a 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Thn... back be~'au'5e VJ 1Y 57 a 0 a a '] 6 0 a 2 ') 9 2 <I 0 I 8 0 13 0 a 0 Ii a 0 a I a 1 1 a 0 0 1 a a 0 0 0 1 0 0 I) 0 a 0 0 a 0 I) I 0 0 0 0 0 () () 0 a 0 a Hard t) cdt('h 5 2 2 7 I) I t a 2 a L 0 0 I 2 2 I 2 I 7 I 2 0 1 I 0 I 0 1 2 2 1 a :) 0 0 0 0 0 0 0 0 2 2 a 0 1 a 0 1 2 1 I 0 0 4 2 0 0 0 0 7
l)an'.ler)\,.oS t'l nanrlle 9 0 9 0 0 0 I 0 0 0 1 2 4 a B 712 Xl 1 1 0 I 010 1 a a 0 0 0 0 0 a a 0 0 0 0 0 0 0 0 0 0 0 () 10 2 ) a 0 1 () I I 2 0 0 I a 0 0 Hard tl C'lG'l" 10 0 a 0 a 0 0 2 0 I 3 1 2 2 5 OJ I 7 9 :) 2 5 4 I I 0 a a 1 1 0 0 0 a 0 a 1 () 0 a 0 I/)O 0 0 1 0 a a 0 1 0 I 1 a 4 a LOa 2
'lust be <;k inned 12 0 0 a 0 0 0 0 0 6 2 0 9 4 7 6 5 7 6 4 0 5 11 0 0 a a 0 a a a I 0 0 0 a 0 a 0 a 0 0 0 a 0 0 a 1 0 2 a 1 a a a 0 a 0 a 0 a 0 S,'avengec F ish sa 0 0 0 0 I a 0 a 4 0 I) 8 8 5 5 .: 5 a I 2 a .3 I ] 0 0 0 0 0 0 0 a 0 0 a 0 a 2 2 I 0 a 2 1 I 1 () a 0 0 t 1 a a 2 I a 0 () I
_-_"_~dib~~-~"!?~-~-*i{~~~-l~~~~e~-oa~~~~~~~[~ ~~ ~ %-~}--&+H-~ ~-~ ~4-H-g+~~-~-~ *-% gg~-%-~4--~~·%+}g g%g~ gH--+-%--~ %-~-t---g--~-t-~-~-%-%-~·%-~ "1eat "'d'5 .) '5tr'")nr~ sll'ld 1 Z7 a 1 0 a a 0 0 0 0 a a a a 2 2 /) ) a a a 0 Ii 2 a 0 0 0 a 0 a 0 0 0 a 0 0 0 f) 0 I 0 a 0 0 0 ) 0 a ~ a 2 0 0 0 a 0 a 0 0 0 0
""eat )n tn~ hard si le 45 0 0 0 a a 0 0 0 0 a 0 0 2 I l \ 2 0 0 0 a a a a 0 0 0 0 0 0 a a 0 0 0 0 0 0 :) 0 I 0 a 0 0 2 I 1 0 0 a 0 0 I) I 2 0 0 0 0 0 Used tl\')stly f)r bi'lit 54 0 0 0 ) 0 2 0 2 a a 0 0 a 0 0 a 0 0 0 0 0 olD 0 :2 0 I a 0 0 0 0 a 0 0 0 0 0 :) I 0 0 0 0 0 a 0 1 0 0 a 0 0 0 () a a 0 a 0 0
.---~-~~!~--E1~~ctaLnT~~f~-~4i~~ 1-;,~7~~ ~-~*-~-%-ri-}-%-g_·g ~+i+%-fr--b ~+g~~-gt+%-%+-g-~ ~ gg-~-%-~-C\-g ~ ~g g~ gg--+-%-~ %--g-~-~-%-%--~-+-~-%--~-%-% Can be aaten 'lnly if sm0ked 40 a 0 0 a 0 a 0 0 0 0 a 0 a a 0 0 0 0 0 0 0 0 0 a 0 0 :) 0 a a a a 0 0 a 0 a a 0 0 0 0 0 0 0 a 0 a 0 0 0 0 0 a 0 a 0 0 0 0 0
""eat i<:; '5tr'in'1y ')(" t lugh 47 1 0 0 a 0 a 0 0 a a 0 0 a 0 a a 0 0 0 a 0 010 J 0 0 0 a a 0 0 0 0 a 0 0 0 a 0 0 0 a 0 0 a a 0 a 0 a 2 0 a 0 () tOO 0 0 ') Oftoan have w')r'11S ·)C i?aCdo;ltes 5610 0 0 I a 0 0 0 0 a a a a a 0 0 0 0 I 4 0 0 a a 0 0 0 a 0 0 0 a a a a 0 a 0 a 0 a 0 0 a 1 0 a :) a 0 a 0 a 0 1 0 0 0 0 0
IXln't ;'?ven ta'5te til(e fish 'j) a 0 0 a 0 0 0 a 0 a a a I 00 a 0100001000 a a a 1000 a a 0 0 0 a a 000 0 f) 0 a 2 0 2 iJ 010 a a a a 0 '1 0 0 Scawngero;, bl.t [)i~'ky "ll)')ut what t'ley r~<1t 60 0 a I 0 1 0 0 a 0 0 0 a 0 1 I I 1 0 0 1 a a a 0 f) a 0 a 0 0 0 0 a a 0 0 a a 0 1 () a 0 0 a 0 1 0 0 0 0 a 0 a 0 2 ') I) f) a 2
Has m\,.od'1y tasta ;:a a 0 0 0 0 0 a a 2 0 a '] 0 0 a 0 0 0 0 0 a 01 0 1 a 0 0 a f) a a 0 a 0 a 0 0 0 0 0 a 0 0 0 0 a 0 0 0 0 0 0 0 0 0 0 I a I) 0 I)
_ Sli'llt ~i-;'" ~-l 000 a a 0 I 0 01 1 a a 1 0 00 a a 1 a I 000 () a 0 0 0 0 a 0 0 a a 2 a iJ 0 ItO 0 1 000 0 0 0 0 0 0 a 0 0 0
Eatert ·tlhen '5maITOi~')~)~~~ ~ J gTggg ggfg"g ~ g6666 01 ~ 6 ~ ~I ~ ~ og-gg ggggg~ ggg ~ g~ g ~ ~ ~~-rr~ -~-f-~ ~ ~ ~ ~ ifr~ ~ ~ g 6a Mc~t te)(tl.re nac,;<! lC grdi.,y 42 0 0 a 0 0 0 0 0 a 0 0 a 0 0 0 0 0 0 0 2 0 010 0 0 a 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 a I 0 a 2 0 2 0 2 I a I I 1 4 a 1 0 a a
Can get ':Jig thick filtH'; lr '5teal(s J5 0 0 0 0 0 000000012206061000000 010000 a 0 0 a 01 000 I 0 \ 042168467) 2 8 sal 000 Hacri flghtlnl fish 5210 S B 2 0 0 3 '] 0 0 \ 0 0 I I 2 3 a 9 2 a q 0 I I 0 0 0 0 i a a 0 0 a a 0 a a 1 2 I I 0 til 1 9 5 4 5 0 a 0 9 6 :) a 0 a a
Stl.rrJy, ,lucable, dln't o;p·)il '1l.l;-Uy 13 0000 a a 0 0000 011102 01102 010 ~O 0 0 a 0 I a a 0 0 a a a a 0 0.3 1 2 3 J.! 4120 ) 012 a 2 a "'eat td)(tve fir'll 4) 0 0 a a 00 0 0 0 0 a a 2 0 0 1 1 0 :) 0 2 0 0 0 0 a a a a a 0 0 0 0 a 0 0 a 0 0 4 1 a a 1 2 4 2 4 2 ) 2 L 1 f) 1 a
6b Vecy fe .... b")n,~s J) 0 a 0 a 0 a 0 0 a a 0 a 2 4 4 1 S J 0 a a 01 1 0 0 0 0 0 a 0 0 0 a 0 0 a a a 0 a a 2 a 0 0 1 7 I) 1 0 2 2 0 0 a 0 0 Can )nly ("') lk )ne Ir t.,,) -Iay<; 13 0 a 0 0 0 a 0 a a 0 a a 0 1. .2 a 1 0 0 0 a a ) 0 a 0 0 0 0 0 0 0 a a 0 a 0 a I III t 1 I 1 1 1 I a 2 I 0 1 0 0 0
~ei'l~ )~'l~h~r:~~~ ~~~~ 1}%-%-g g-~*~ ~ ~ g~-~ ggg~ ~ g~ gg ~ gggg.%-~ ~ ~ ~-~ gg~ gg55~+~H·l~ 6·~6h'-~~g~~+~6-*~g-i--g ~ gg Mu<;t CI,t ')\,.ot re,j stced~ fnm Ille.'lt 49 0 0 a 0 0 0 0 a a 0 a 0 aLl a lOt 0 0 °10 0 0 0 0 a 0 0 0 0 a 0 0 a 0 a 0 a a 0 a 0 012 a ) .3 ) I \ 0 0 0 0 0
Meat jarl( wnen rd"" 2S I a 0 5 a 0 0 ] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 a a a 0 a 0 0 a a 0 0 a 1 a 0 1 a 0 0 7 0 2 1 0 0 a 0 a 1 a 0 a 0 0 61,) ldy meat 2) a 0 0 4 0 0 0 ] I 0 0 1 0 0 0 0 a 0 I I a 01 a a 0 0 a 0 0 0 0 0 a 0 0 0 a 0 a 0 0 0 0 0 a 5 I 0 I/) I 0 a 0 a a 0 a a a
r'eat tao;t(H f i'5ny 19 1 a 0 0 0 0 a a 0 0 a 0 0 () 0 a 0 0 0 0 I I 6 0 0 0 0 1 0 0 0 0 a 0 0 a 0 2 ) a 1 a 0 1 7 0 I 0 a ) 0 a a a a I 0 0 0 a Meat 'li Iy ta-Hill1 11 0 a a 0 0 0 a 0 0 0 0 0 I a a 0 a 0 0 a a ')15 0 a 0 a a 0 a a 0 0 0 a 0 0 0 0 1 a I I I :2 7 a 2 ') 0 LaO 0 0 0 0 0 1 0 0
Medt '5tr"mg t"l,,>tir"lg 22 i () 0 0 0 0 0 0 0 0 a 0 I 0 0 0 2 a 0 0 a 2 4 0 0 a a a 0 0 0 J u U 0 a a a 0 1 0 1 0 I 0 8 0 ) 1 0 a 0 1 0 0 1 I a 0 0 0 ___• __~ "__ Are ~est Sm')k_~ 19 0 0 0 0 0 a 0 0 0 0 0 a 0 0 0 0 0 0 1 0 0 0\ 5 a a 0 0 0 0 0 a 0 0 0 a 0 0 a a I 0 1 a a a 5 0 4 0 0 0 0 0 0 0 0 0 a a 0 0
Figure 8.-North Carolina sorted item-by-use matrix based on row-row and column-column similarities.
Marine Fisheries Review 134
'1ost r>e''}ple o1at I pcef~r t'l catt"h
Easy to) ("lean Mea.t has "'111 taste
la '1ea t wh i to when c"')')ke d Meat ..,hite Ioi'hen caw
Can c'll)k any way y,,>u 1 ike easy t'1 pcepare
IIp..:.tt texture tender Nice flaky meat
l 1 l l l Car) get hig thick. fillets ,r c;t~aks JS 2 0 0 0 01 0 0 0 0 0 0 0 6 5
Hard tl) catch 5 2 2 l 2 2 l l 2 5 l , fiard fightirq fic;h 52 9 6 5 7 9 5 l 0 0 0 0 l , 6
Easy t,) t'atch 6 3 l l 3 01 3 2 l l 3 6 , l 2 0 lO Fhtt'1m feedecs 6l l l 2 l l l 6 l 3 l 6 5 3 J
Sturdy, ducitble, d ..esn't <;p'111 'luickly l3 2 2 2 2 21 ? 2 2 2 2 2 2, 5 , , , 22Sl imi f ic;" 56 2 2 2 2 2 Bll 2 2 ? ~·)t sturdy, dl.rable, <;[)0ils easily l4 5 , , , 'I' , , , , , , 6, 2 , 3 2 ,
6, , 3freeze ~e 11 16 2 2 2 ] 2 2 2 l l 1 l l2 2 l l~"l"l'-------------...,.,Mo'"'s~t;:.~~l~e.~~u~~tf~:'~ 2 =ra 91111 11 91211 6 3 6 8 9 9
I hOl ....e never teien e:!lti"l] "O 9 to II III 6 7 <J 10 8 9 8 6 6 9 ')anger )l.S t·) handlA 9888887 8 l 0 III 9121211
Must be c;k inr'\~<i l 0 0 , 9 8 7~J6gggglg o 6
fiard t") clean l 0 0 8 6 6 5 Edibl"!, blot thece 'lre b~tter fish t'1 Ite~p 62 2 1 1 2 01 1 3 1 6 2 5 2 6 5 4
6 6 5 4 "
---------~--East~~hen~~~~r<;~~~~ ~ 6~ ~ 661 ~ ~-~-H l~ 2 0 0 0 ::dll 'levee get bi!] thicl{ fillets )(" c;tedl(<; 36 0 1 0 1 1 0 0 1 2 3 1 o 0 0 0
\I0t 'li.lc1 fight in.) fish 530000010021'0 o 0 0 0 Small 'nn·::c; 3203000000120 o 0 0 0
(f)')d (Ht'\ ~ ish 34000001000100 o 0 0 0 10'1 <;m3ll t·') bqther with 5401000000103 2 0 0 0
13'lny ll03,Oq,0020, 1 0 0 0 Only eitten by certai" cld.5!>es 'JE peJple 5000200010302 2 2 2 1
DJe'i n'1t freeze .-Ie 11 15000001000000 o 0 0 0 Meat In the 'i'Jft 'ii,],~ 4400000000000 o 0 0 0
-------~eaten ?ec'luscril'lo/),,·.:Il';s 20000001617001 l l 0 0 Thr'") .... back t)eC'lu<;e ufJly 5700000030600 o l , l
T",c;te'i 1 ike i Jdinf1 2300000\000lOO 6 l l 0 Melt is <;tcin'JY 'Jr t0t.qh 4700000000000 o , l
Scave"'Jers, but 9icl(y <lIh"lut what they eat 60000001000l00 0 I l l Has 'Tll.drly taste :EQ,OOOOOOOlO2 l 0 0 0
Dnesn't eve" t",c;te lik~ fis'l 50000001000000 1 0 0 0 Used rrnstly f'1r bait o 0 0 0
__•• • ~~!!.~~~~jl~_kl~.j ~~bb~~I~~~~~~ o 0 0 0 J=:ate" .... hen small, n")t big 7 0 0 0 10200000 o 0 0 0
') 'leat texture coar<;e )r <]rainy 42000001000000 0 1 0 0 Oftl:O!n have ....·Jrms .,r parasit<:l<; 9600000000000 o 0 0 0
--------------------t1eat taste<; fishy 19 0 0 0iggnggg6gi 1 l1il] b'med 3l l 0 l 0
Very few b')rH~<; o l 2 l '1n ly C·J·JOe. 'Jne Jr t"') ways ~g~r~?lg6ggrg l l lCan l
Are best <;m'10e.~1 362 l l l ill l l l I l l l l l -----------;::tL;st~~e:rbehrec')'1kln;l 1700000000000 o 2 3 2
'1eat h-l$ a 'itt" In<J sme 11 o 2 3 2 "1e-lt )0 the hard s i.de ~~~bigl;ggggg o 0 1 0
~1ed.t '>11y ta:;tinq 2l l 0 3 lOIOOOlOO 0 I l l ~leat 5t,. In'J tast i"J 22 0 0 1 30000000 o l I l
''1eat ,1ark when ro'l .... :5305601°00000 o 0 0 0 '31')'1dy '!leat 23316')1100102 I 0 I 0
11lJc;t ct.t <1l.t re.l .;trea~ fr'1'" meat 49101001000000 o 0 0 0
'" 1.0 '"' I'"'
.0 U
u'"U'" '"
l l l 2 6 l l l 2 l l , l l 2 l l l l l 5 l l 5 , l l , l I l 0 0 l l l 3 0 l 2 l 2 0 0 l 'l 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 7 3 6 , 9 , 0 l l 0 0 5 0 , 3 lO 2 °1'0 0, 0 1 0 l l l 0 0 l 0 0 0 0 0 l 0 0 0 0 5 5 l 3 5 5 l I , l l l l l , 7 2 9 3 2ll 7 0 l 0 l Oi' 2 , 0 l l l l 0 0 0 0 0 0 2 0 l 0 l l l I l I 2 3 7 75 5 6 5 2 51' 3, l , I l l 2 l , l 2 2 l l l l l l l l 2 I 2 l l l , 5 l l I 2 5 9 lO l , 5 7 71 2, , , 2 2 21 2 2 2 2 2 2 , 2 2 2 2 , , , , 3 3 3 3 3 , , 2 , 2 3 3 5 3 2 , B , '1 3 3 2 , 2 2 2 2 2 2 2 , 2 , 2 , 2 2 , 2 2 2 2 3 2 '- , , , , 3 1 , 3 , 3 5 , 2 , 3 , 3, , , , ,
'I' , , , , , , , , , , , , , , , , , , 5 , , 5 6 7 5 , ') 610 9 , , 'I' ,
3 3 223 2 2 2 2 3 2 2 , 2 , 2 ? 2 , 2 2 2 2 2 , 3 , 2 3 , 6 7 5 6 510 4 4 3 3 l l l
~-iL; l l 2 l , l l l l l l 1 1 3 3 l l 3 3 3 l 2 l 2 3 3 , , 6 'll 2 _tl.L.~ 2 , 5 6 7 7 7 6 6 , , 5 6 6 6 -6 3 2 3 l l 0 , 0 l 0 l , 3 o 0 0 l 0 l 5 2 3 6 , 7 g 61 g
9 9 7 8 7 8 7 9 7 6 5 6 6 6 6 5 3 3 2 2 l l 3 3 3 l l 0 0 o 0 5 'I' 2 0 0 0 0 0 l 3 0 0 l 0 0 0 0 0 0 l 2 0 0 3 0 l 0 0 0 0 0 0 l 0 l l 0 o 0 5 0
~ gl g 0 l 0 0 0 0 0 0 0 0 0 0 0 0 0 0 l I l l 2 2 0 0 l 0 0 l 3 o 0 l l 3 0 q 6 , 0 0 0 0 2 l 0 2 0 0 0 0 0 0 0 0 l 0 0 0 0 0 l l 0 0 0 0 2 o 0 0 o 3 4 7 2 0 0 0 l 00100"0300000000 2 0 0 0 00000002 :J 0 0 0 I 0 7 91 2 2 l l l 1 I 1 3 1/.221 I 111 1_~ _i_I_'.t +~-.!-~_'_'3+l-~-} 3 ~ 1 2 0 0 l 00j00-0(j()T006ooo-0 0 1 0 0 0 00002003 432262 02]000 0 l 1000211110010000 a 0 0 0 o 0 0 0 3 1 1 2 7 1 7 2 4 0 1 4 0 3 l l l 11102131320000000 o 0 2 0 o 1 1 3 2 0 1 2 2 '5 5 1 3 0 l ,[ 0 0 0 0 2 0100100100000000 o 0 0 0 00000004 'J 0 6 1 1 0 1 0 1 1 0 0 l OOIOOOOOlOOOOOOOO o 0 0 0 00000223 o 1 1 4 3 0 o 01 0 0 0 0 2 0003010100000000 o 0 0 0 00000002 000010 o 0 0 0 0 0 0 I qOl010000000000 tOo 0 00000002 6 0 3 0 t 0 , 'I' 2l 0 0 1011201000000000 o 0 0 0 10001002 2 1 0 1 1 2 4 0 0 0 0 0 0 00100000000000000 o 0 0 a 01000231 o 0 3 1 5 0 o 01 0 0 0 0 l 0000000000000000 o 0 0 0 00001220 000000 o 0 0 0 ° 0 0 0 0 a ~g'ggA~~~~~g~gggg o 0
o 0 0 0 00000000 000000 g ~I g ~ 0 0 00000000 000000
0 o 0 00100000000000000 o 0 0 0 00000000 000000 o 01 0 0, 0 o 0 0000000000000000 o 0 0 0 00000000 (100000 2 () 1 0 0 o 0 00100000000000000 o 0 l 0 10000000 o 0 1 0 1 1 l 11 0 0 0 o 0 1000000000000000 o 0 0 0 00000000 000001 o 0 0 0 0 o 0 00100000000000000 o 0 0 0 20110000 010000 o l[ 0 0 0 o 2 0 o 0 ~~Igbggg~gggbgggg o 0 0 0 00000000 1 0 0 0 1 0
g gl g go 0 0 0 00000000 000000 0 o 0 0000000000000000 o 0 2 0 0 l 100000 000000 9 1 2 0 0 o 0 00100000000000000 o 0 1 0 00100000 000003 6 31 3 0 0 o 0 0000000100000000 o 0 0 0 00000000 000003 12 2 0 0 0 o 0 i gl g 6~ g g g ~ g g g g g ~ g
2 0 OOlOuOul u 0 0 l l : ~ ~I ~ ;o 0 o 0 3 l 11100000 o 0 1 0 1 0 o 0 001'0000000000 000 o l I 0 3 2 3 0 0 0 1 0 13] ) 21 o II 3 2 l l l l l l ~ ~I ~ ~ ~ ~ ~ ~ ~ iii i ~ i i l l I l \ 1 1 1 1 112 324112 ; ~I ~ ~l2 l l 1 I 1 1 1 III 111111 0 o 0 0000000000000000 l 0 0 0 00000000 o 0 0 0 0 1 0 0 5 1 0 o 0 ggl~ggggggggggggg o 0 0 0 00000000 000010
~ :' i i 0 o 0 l l I 0 01100000 010000 0 o 0 o Oi' 0000000000000 2 0 0 0 00000000 000000 o 'l 8 7 0 o 0 00 I 0 I 00000000000 , I 0 0 00100000 000000 2 2 9 7 0 o 0 ggl~ gggg; ggg; ggggo l 0 l 1 1 I 0 1 0 0 1 000001 o 'l'o 7 0 o 0 o l 0 l 00000000 000001 o 0 <} '5 0 o 0 00\00000000000000 o l 0 0 3 1000000 o 0 0 1 o , o 61'0 ,
Figure 9.-Texas sorted item-by-use matrix based on row-row and column-column similarities.
49(2), 1987 135
II.
NICE FLAKYFigure ll.-Implicational relationships l-'EAT
among positive belief-frames.
cluster
cluster I.
CflLvEATErleV 'VRD TO CERTAIN CLASSES I"EAT HAS A
Cl.UJ I OF PEOPL£ STROl'G Sl"iLl0/{ATr::-\ OILY TASTING
CArl ONLY COOK ONE 00 'TY(l
,",vs
H.AAD FIGHTII.G FISH cluster
Figure l2.-Implicational relationships among a separate set of more
negati ve belief-frames.
Figure 1O.-lmplicational relationships among negative belief-frames.
I'bST PEOPLE EAT
r II.
Figure l3.-Contrast relationships among belief-frames. Lines with cross-hatching
indicate the contrast relationships.
Marine Fisheries Review 136
of uncertainty; had fishermen actually eaten and rejected these fish, our task would have been much more difficult. In addition, this information helps establish parameters for determining an approach for enhancing the image of a particular underutilized species. Knowing what positive attributes to stress, and in what combinations (e.g., knowing the importance of the implicational relationships between "nice flaky meat," "meat white when cooked," cook any way you like," and" easy to clean"), can make a considerable difference in promoting fish. Similarly, and equally important, knowledge about negative attributes and their perceived relationships can help in determining appropriate ways to deal with the negative attributes of a particular species.
Discussion and Conclusions
These findings suggest that most perceptions concerning underutilized species are developed outside actual experiences. Beliefs relevant to these species are generally the result of hearsay and rumor perpetuated during a fisherman's socialization into recreational fishing. Ambiguities about the perceptions of underutilized species and lack of experience with such species are cognitively dealt with in terms of the general ways that recreational fishermen rank and classify fish.
Many of the findings of this study came as no surprise. That recreational fishermen target fish they perceive to be fun to catch, good to eat, easy to cook and clean, etc., are not earth-shattering revelations. Yet we would have suspected our techniques and interpretations had we not confirmed such banal knowledge. In many ways, this confirmation lends confidence to our findings.
This analysis has placed species of saltwater fish in relation to one another in terms of their similarities and differences as perceived by recreational fishermen. This information has served as the foundation for the development of educational/advertising materials designed to improve the reputations of underutilized
species, thereby promoting their use. The methods used in the study complement one another in this regard. While the HCL yielded an understanding of the general perceived similarities and differences among species, the MDS further defined relationships between the species in terms of the specific dimensions of sportfish and meatfish. These relationships suggest possible ways that underutilized species' images may be improved via favorable comparisons with preferred species that, in the minds of fishermen, they already resemble. These relationships between species also suggest which underutilized species are the most and least likely to improve with an educational program. The item-by-use matrices and entailment analyses further defined relationships between the species in terms of attributes suggested by fishermen. An understanding of the relationships between attributes (belief-frames) suggests the proper and most appropriate ways to present a case for the increased utilization of underutilized species within an educational context. Together, the three types of information provide a clear and workable picture of the domain of saltwater species as perceived by people who regularly and actively deal with them.
Knowing what fishermen like or do not like and understanding the manner in which they express their beliefs concerning fish is critical for producing appropriate and effective educational materials. In Part II, (Murray et al., 1987) we look at the application of this information to the development of educational materials directed at encouraging marine anglers to better utilize nontraditional fish in the southeastern United States.
Literature Cited Bell. F., P. Sorensen, and V. Leeworthy. 1982.
The economic impact and valuation of saltwater recreational fisheries in Florida. Fla. Sea Grant Coli. Program. SGR-47, 130 p.
Berkes, F. 1984. Competition between commercial and sport fishermen: An ecological analysis. Human Ecol. 12(4):413-29
Burton, M. 1972. Semantic dimensions of occu
pation names. In Romney, A. K., R. N. Sheperd, and S. B. Nerlove (editors), Multidimensional scaling. Seminar Press, N. Y.
.D'Andrade, R. G. 1976. A propositional analysis of U.S. American beliefs about illness. In Basso, K. H. and H. A. Selby (editors), Meaning in anthropolgy. Univ. New Mex. Press, Alberquerque.
____, N. R. Quinn, S. B. Nerlove, and A. K. Romney. 1972. Categories of disease in American-English and Mexican-Spanish. In Romney, A. K., R. N. Shepard, and S. B. Nerlove (editors), Multidimensional scaling. Seminar Press, N.Y.
Johnson, J. c., and D. C. Griffith. 1985. Perceptions and preferences for marine fish: A study of recreational fishermen in the southeast. UNC Sea Grant Rep. 85-01, Raleigh, N.C.
____, , and J. Murray. In press. Recreational fishermen's perceptions and preferences for marine fish: Some methodological considerations. In Proc. Gulf Caribb. Fish. Inst.
Johnson, S. C. 1967. Hierarchical clustering schemes. Psychometrika 32:241-253.
KCA Research. Socioeconomic aspects of marine recreational fishing. 1983.
Kruskal, J. B. 1964. Nonmetric multidimensional scaling: A numerical method. Psychometrika 29: 115-129.
Murray, J. D., J. C. Johnson, and D. C. Griffith. 1987. Encouraging the use of underutilized marine fishes by southeastern U. S. anglers, Part II: Educational objectives and strategy. Mar. Fish. Rev. 49(2):138-142.
Romney, A. K., R. N. Shepard, and S. B. Neriove (editors). 1972. Multidimensional scaling: Theory and applications in the behavioral sciences. Vol. 2. Seminar Press, N.Y.
____, T. Smith, H. E. Freeman, J. Kagan, and R. E. Klein. 1979. Concepts of success and failure. Soc. Sci. Res. 8:302-326.
Schoepfle, M., M. Burton, F. Morgan. 1984. Navajos and energy development: Economic decision making under political uncertainty. Human Organ. 43:265.
Stefflre, V. J. 1972. Some applications of multidimensional scaling to social science problems. In Romney, A. K., R. N. Shepard, and S. B. Nerlove (editors), Multidimensional scaling. Seminar Press, N.Y. 1971.
---,---,c:--' P. Reich, and M. McClaranStefflre. Some eliciting and computational procedures for descriptive semantics. In Paul Kay (editor), Explorations in mathematical Anthropology. MIT Press, Cambridge.
USDOC. 1980. Marine recreational fishery statistics survey, Atlantic and Gulf coasts, 1979. U.S. Dep. Commer., NOAA, Natl. Mar. Fish. Servo Curro Fish. Stat. 8063, 139 p.
Weller, Susan C. Cross Cultural Concepts of Illness: Variation and validation. American Anthropologist Volume 86, #2, pp. 341-350. 1984.
White, D. R., M. L. Buron, and L. A. Brudner. 1977. Entailment theory and method: A crosscultural analysis of the sexual division of labor. Behav. Sci. Res. 12:1-24.
49(2), 1987 137