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A Review of Ecological Determinants of Territoriality within Vertebrate Species.


ABSTRACT.--We reviewed papers that compared intraspecific variation in territoriality vs. alternative forms of spatial or behavioral organization with three goals: (1) to discover which ecological variables act as determinants of territorial behavior and how they might act; (2) to extract and evaluate predictions and evidence for determinants of territoriality and (3) to suggest ways for future studies to build upon what the review revealed. Twenty ecological variables have been predicted, correlated with or experimentally demonstrated to relate to territoriality within vertebrate species. These variables include several characteristics of food: quantity, predictability, distribution, quality, renewal rate, type, density and assessibility. Other variables include nonfood resources, population density, habitat features, mates, space, refuges/spawning/home sites, predation pressure, host nests (for brood parasites) and energy availability. We suggest several reasons why food resources are cited most often, incl uding their biological significance, ease of study and publishability of negative results. Certain groups of animals lend themselves to certain methods of study and, therefore, constrain the variables measured. Many variables are the subjects of apparently contradictory reports, i.e., some papers report that an increase in a given variable increases territoriality and others report that a decrease in the variable increases territoriality. After summarizing these reports we hypothesized U-shaped relationships between the ecological variables and behavior that could accommodate all these findings. However, these hypotheses cannot be tested rigorously by most current studies because of methodological limitations. We recommend a shift to quantification of intraspecifically varying spacing systems combined with simultaneous quantification of several ecological variables. Relative importance of different determinants of particular spacing systems can be revealed via multiple regression analysis. Hypothesized causal pathways, in which one ecological variable determines another variable that, in turn, determines territoriality, can be tested by path analysis.


Many studies have analyzed the ecological variables determining whether a vertebrate population expresses territoriality or an alternative form of spatial organization. Grant (1993) reviewed some of this literature, primarily that on fish, but no one has reviewed this large volume of information for all vertebrate taxa to synthesize and evaluate the collective data.

This paper has three goals. The first goal is descriptive. We report the ecological determinants of territoriality proposed and studied; research approaches taken and species studied. We asked: Are variables predicted to determine territoriality different from those correlated with the spacing system? Which variables have causal effects? Are the same variables cited for all taxa?

The second goal is synthetic. To extract the maximum available information about relationships of specific ecological variables to territoriality, both in the investigators' thinking and in their data, we compiled the literature by individual ecological variables or combinations of variables. We evaluated the strength of the empirical evidence and we attempted to understand why some studies reported a different relationship than others, e.g., large amounts of food lead to territoriality vs. abolish it. When authors proposed a causal pathway in which one variable changed another which then determined a spacing system we recorded the pathway and asked, do authors expect these intervening variables to affect spatial organization in similar ways, e.g, do authors agree on how food quantity is expected to alter intruder pressure and how intruder pressure then alters territorial behavior?

The third goal is methodological. We take what we learned about the evidence and methodological issues and recommend more emphasis on the use of multivariate statistics to analyze relationships between quantified ecological variables and quantitatively described social systems.


We attempted a complete search of the vertebrate literature, with no restrictions on time period or journal, to find papers meeting several criteria. We chose papers in which the authors attempted to understand vertebrate territoriality by comparing differences in ecological conditions with intraspecific differences in social organization. Populations could be spatially separated groups of conspecifics or they could be the same group of animals studied at different times, e.g., before and after manipulation. Because we wanted to explore differences in social organization, we examined papers that addressed presence or absence of territoriality rather than changes in territory size (e.g. MacDonald and Carr, 1989). Since leks are small compressed territories, we excluded reports of large territory vs. lekking populations (e.g, Clutton-Brock et al., 1988).

Territoriality has been defined many ways (reviewed in Maher and Lott, 1995). We propose the following definition of territory: a fixed space from which an individual or group of mutually tolerant individuals actively excludes competitors from a specific resource or resources (Maher and Lott, 1995). Relatively few authors operationally defined territoriality so we usually had to rely on conceptual definitions of territoriality. We included papers using a stated or implied definition of territory as a defended area and/or an area of exclusive use. In species or situations where defense is difficult to observe (e.g., small carnivores) territory sometimes is inferred from exclusive use (Maher and Lott, 1995).

In the papers we selected authors identified environmental variables believed to be responsible for differences in spacing systems. We primarily used the authors' terms for environmental variables or we followed Warner's (1980) definitions of food density, variability and predictability. We excluded demographic variables, such as age distribution and sex ratio, that pertain to the population itself. Since population density often is determined by external environmental conditions we included it in the review.



We placed papers into one of three categories depending on the type of relationship between the ecological variable and spatial organization. (1) Authors predicted, a priori, that territoriality would be determined by a specific ecological variable (e.g., Armstrong, 1992), yet authors may or may not have tested these predictions. Predictions reveal an author's thinking, but they are not evidence, and we report them simply as predictions. These studies are indicated by the symbol [P] after the citation. (2) Authors interpreted data about specific ecological variables as being correlated with territoriality (e.g., Fitch and Shapiro, 1990). Correlations between a variable and territoriality provide more compelling evidence than predictions alone. These studies are indicated by the symbol [C] following the citation. (3) Authors experimentally demonstrated that an ecological variable determined territoriality, usually by manipulating the variable and observing which spacing system was expressed (e.g. Ims, 1988). These studies provide the most compelling evidence because they test causal effects and because investigators usually control all but a small number of variables. They are indicated by the symbol [E] following the citation.


Twenty variables were cited as influencing the expression of intraspecific territoriality, and more papers presented evidence of correlations between variables and spacing systems than demonstrated or predicted the relationship (Table 1). Fifty-five percent of papers reporting experimental manipulations cited at least one of three variables: food quantity, food distribution and population density. Food, and its many subcategories, were universal factors; they were predicted, correlated with and experimentally demonstrated to affect spacing systems. The broad heading of food included eight variables: assessibility (degree to which food characteristics can be monitored by individuals), food density (quantity of food per unit area), distribution (degree of patchiness or aggregation), predictability (degree to which food patches are dependably available), quality (nutritional characteristics), quantity (amount of food available), renewal rates (degree to which the resource is replenished per unit time) and type (diet, such as fruit or insects). Food quantity was cited in more papers (24%) than any other ecological variable and appeared in each category along with food distribution, predictability, quality and renewal rate.

Perhaps these patterns reflect the authors' approaches to the study of spacing systems. Relatively few studies (23%) manipulated ecological variables and observed the effects on spacing systems, probably because of problems associated with demonstrating causation (e.g., controlled conditions in field settings). Whereas food quantity, food distribution and population density may be the most important variables, the logistics of field experiments also may explain why these variables were tested most widely.

The importance of food in determining spatial organization may be overplayed (Stamps, 1994). Because ease of study is a confounding factor in studies of food importance, we cannot use frequency of study as a reliable guide to biological significance. Obviously, food is an important resource for animals and it is relatively easy to quantify and manipulate. Furthermore, animals usually are most conspicuous when they feed and much behavioral data can be collected at that time. Whereas the importance of food has been studied in many species, some of the best developed analyses of territoriality have been conducted in nectarivorous birds, perhaps because food and energy expended in defense are quantified easily in calories and because energy from food is manipulated easily (e.g., honeyeaters, Phylidonyris novaehollandiae and P. nigra: Armstrong, 1992 [P, E]; McFarland, 1994 [E]; Hawaiian honeycreeper, Vestiaria coccinea: Carpenter and MacMillen, 1976 [P, C, E]; review: Carpenter, 1987 [C, E]; golden winged sunbir ds, Nectarinia reichenowi: Gill and Wolf, 1975 [C, E]). Because of the physiological demands of nectarivores, food probably is an important determinant of spacing systems in these animals; however, broad generalizations to other taxa, e.g., ectotherms, may not be justified.

Food could be seen as the most important ecological variable if it explained most of the statistical variance in experimental results. However, few investigators examined the amount of variance explained by each ecological variable. Also, many variables are not independent of each other. Analyses such as partial correlation or multiple analysis of variance can be used to assign relative importance to quantified variables, but relatively few researchers quantify ecological or behavioral data.

Another reason for the apparent importance of food may be related to the "file drawer problem", i.e., positive results tend to be published more often than negative results (Csada et at., 1996). For example, if a researcher manipulated food and observed no change in the spacing system this could indicate food was not important but that other unknown factors were relevant. These results probably would remain unpublished and further bias the literature. Until recently, only a few papers made predictions or manipulated variables and reported negative results; however, more papers reporting negative results now seem to appear in journals. For example, even in nectarivorous birds, experiments do not always find that food determines territoriality. Experimental studies of honeyeaters that examined relationships between territorial defense and nectar quantity and between nectar levels and intruder pressure did not find causal links between these variables (Armstrong, 1992 [P, E]; McFarland, 1994 [E]). Although beha vior patterns changed, territoriality did not disappear as a result of food manipulations. Hofer and East (1993 [C]) also concluded food was not an important determinant of territoriality in spotted hyenas (Crocuta crocuta) at their study site. These data do not contradict reports that food acts as the controlling determinant in other circumstances. They do not even show that food was unimportant in these particular circumstances. Rather, they suggest that its importance sometimes is overridden by other variables. Negative results may contain as much information as positive results, and biologists are becoming more sophisticated at incorporating them into bodies of knowledge (e.g., by evaluating their significance via power tests).

Less easily measured subcategories of food are studied less often (Table 1). Food quality is difficult to assess, especially in the field. Even predictability can be hard to quantify: what criteria does an animal use to gauge how predictable its food resources are? Likewise, whereas food distribution can be manipulated to some extent, it may be difficult to measure since it can vary temporally and/or spatially (Pielou, 1969). A researcher first must determine which scales are relevant to the study organisms (i.e., one might expect the relevant scale of distribution of food over space and time to be smaller for an herbivorous pronghorn, Antilocapra americana, than for a carnivorous coyote, Canis latrans) then quantify food distribution over appropriate temporal and spatial scales.

To understand better why populations are territorial future studies should examine factors other than food, including habitat features, population density and predation pressure. For example, Pyke (1979) proposed several models to explain sunbird territoriality relying exclusively on measurements of calories available from food and calories and time spent in various activities. However, his models did not include predation effects. Certainly, testing the relevance of predation pressure will be difficult (Isbell and Young, 1993), yet several authors predicted predation should affect spatial organization and/or correlated predation with expression of a spacing system (Case, 1978 [P, C]; Myers, 1980 [P, C]; Kavanagh, 1981 [C]).


We next explored relationships between studies of ecological variables and vertebrate taxa which included bony fish, amphibians, reptiles, birds and mammals. We present the data in two forms: by species (Tables 2-5) and summarized by class (Table 6). Just 26% of papers reported on ecological determinants of variable spacing systems in fish, amphibians and reptiles and 11 variables out of the 20 reported have become candidates for determining territoriality in those groups. However, certain variables such as population density, predation pressure, habitat features, space, mates (including their density and distribution) and home/shelter sites can be applied broadly to many species.

Population density and space were cited as determinants of territoriality in 31% of fish papers, perhaps partly because of the use of aquaria in fish research. Manipulations generally involved changing the size of aquaria (space) or adding or subtracting the total number of fish in aquaria (population density). Researchers can seldom change experimental conditions so easily with other vertebrates. Population density was reported in just 7% of bird papers. Perhaps other density dependent factors operate to influence territoriality or birds may choose other options when habitat is too crowded, e.g., not breed, disperse or stay and help raise breeders' offspring (Brown, 1987).

Make distribution and mate density were considered in only one reptile paper (M'Closkey et al., 1987 [E]), one fish paper (Grant, 1997 [E]) and a few mammal papers (Liberg, 1984 [C]; Ostfeld, 1986 [P, E]; Ims, 1987 [C], 1988 [E]; Carranza et al., 1995 [E], 1996 [C]; Nelson, 1995 [C, E]); they were absent from bird and amphibian papers. In mammals, a male's territory may overlap several females' home ranges. Some birds show a spatial distribution similar to mammals; however, females generally settle in territories that males already have established. Also, for many birds, the sex ratio is skewed little, if at all. Many mammals have a highly skewed sex ratio and a higher incidence of polygyny; thus, a male can defend several female home ranges as his territory and gain exclusive access to them.

Contrary to the limited treatment of mates as ecological determinants of territoriality in much of the literature, Grant (1997) reported that fish defend mates and spawning sites more often than they defend food. He suggested that spatial distribution of mates and spawning sites can be clumped in a smaller area during the relatively short reproductive season, and this is more defensible than food, which is more widely distributed and must be defended for more than one season.

Some authors reported variables that appear important for a particular species (e.g., host nest availability in brown headed cowbirds, Molothrus ater, Elliott, 1980 [C]; and spawning sites in coral reef fishes, Dubin, 1981 [C]; Robertson, 1981 [C]). These variables could be examined in similar species to determine if they can be applied across taxa.


Earlier we explained that, depending on the type of data, we assigned papers to one of three categories: predicted, correlated or experimentally demonstrated relationship. In our view any one interpretation of these data becomes less compelling as the number of likely alternative interpretations increases. Two major sources of alternative interpretations are unnoticed causes of correlations and phylogenetic inertia.

Unnoticed causes of correlations are variables that determine territoriality but that the investigator does not record. For example, perhaps territoriality actually was determined by higher population density, but the observer recorded food quantity only and thus attributed increased territoriality to increasing food levels. This potential error is inherent in any design in which one variable is correlated with one or more other variables. Such studies cannot discover if the correlation represents causality. A spacing system probably is determined by multiple factors with no one variable accounting for all the variance and perhaps not even most of it. Consequently, when fewer variables are considered in a correlative study, it is more likely that other unrecorded variables actually determine the spacing system.

Unnoticed causes of correlation are less problematic in controlled experiments where only one variable is manipulated. The effects of such a variable can be seen separately, and the interpretation that the variable at least partly determined territoriality is not ambiguous. For example, the failure of males to establish territories when Ims (1988 [E]) experimentally placed grey sided vole (Clethrionomys rufocanus) females in a clumped distribution demonstrated that another variable, perhaps higher intruder pressure, was overriding resource distribution. Likewise, when Nelson (1995 [C, E]) found no relationship between female spatial distribution and territoriality in male field voles (Microtus agrestis), the effect of female density in producing more exclusive male home ranges apparently was confounded by the positive correlation between home range size and amount of overlap.

Phylogenetic inertia is another alternative explanation of data. Territorial behavior may be seen in two groups of animals because of genes they share through descent from a common ancestor rather than because of one or more shared features of their ecology (Alcock, 1998). Furthermore, territorial behavior may not be seen in two groups, despite their sharing critical features of the ecology, because they have inherited different genetic predispositions (Alcock, 1998). The possibility of phylogenetic inertia, and other issues of evolutionary vs. ecological vs. behavioral time scales and of fixed vs. plastic responses, often can be eliminated as explanations by studying animals that show intraspecific variation in social systems. Lott (1991), Shapiro (1991) and Warner (1991) discussed advantages of intraspecific variation as a tool in behavioral ecology, and those systems will generate the strongest evidence of ecological determinants of territoriality. We acknowledge that many, perhaps most, species are not p lastic enough for research on them to yield the most compelling data and, accordingly, recognize the value of interspecific comparison (Barlow, 1993) as the only feasible approach for many species. At the same time, we believe researchers cannot achieve the same level of certainty about ecological determinants of territoriality in those species compared to more flexible species.

Many studies we cite were designed to investigate the role of a particular ecological variable in the territoriality of a particular species in a particular situation. In doing so, authors provided evidence that many ecological variables act as determinants. But if many different variables determine territoriality, no one variable is likely to determine it every time, and unrecorded variables will produce apparent contradictions. Our first reaction to studies that did not agree about determinants was that one must be right and the other wrong, and if the numbers of pro and con reports were similar, perhaps the contradiction could not be resolved. Certainly, some papers provide weaker data than others do. For example, some of the older literature relies more heavily on a descriptive rather than a quantitative approach (e.g., Snow, 1956 [C]; Young 1956 [C]; Prior, 1968 [C]). Furthermore, whereas some authors quantify ecological variables, they do not quantify territorial behavior (e.g., Smith, 1968 [C]; Prieto and Ryan, 1978 [P, C]; Rothstein et at., 1984 [C]). Even when variables are quantified two authors rarely measure the same variables in the same way. Despite these problems, however, most authors probably are correct about their findings. Thus, we regard negative reports as supplementing, rather than contradicting, positive reports.

Finally, whereas many papers report on particular taxa, we chose to try to synthesize the literature by focusing on similarities across taxa. Findings usually crossed taxonomic lines, suggesting substantial similarities among disparate species.


Whereas most authors implied or used the "economic model" (Brown, 1964; Stamps, 1994) which assumes individuals should exclude others from nonshareable resources if fitness benefits exceed costs, we do not discuss the cost-benefit analyses that provide an adaptive justification for the predictions and correlations. Many people have discussed this rationale, e.g., why it pays an animal to defend a resource at intermediate levels of abundance but not at high or low levels (e.g., Brown, 1964; Wittenberger, 1981; Krebs and Davies, 1993). Alternatively, researchers could employ an Evolutionarily Stable Strategy or game theoretical approach, which emphasize fitness consequences of behavior, to understand why spacing systems vary. Yet, whereas many investigators have reported on ecological variables affecting a particular spacing system, few (if any) authors have measured the fitness of animals under particular spacing systems. This approach, while rarely taken, should prove profitable, even though measuring fitnes s has its own difficulties (Krebs and Davies, 1993).

We chose to focus on determinants that are discussed most often or determinants for which the apparently contradictory evidence indicates a complex relationship that would merit further analysis. Unlike Grant's (1993) review of fish, we did not treat all resources as equivalent since some have different properties than others. We designed the following discussion to be browsed, much like a table, rather than read as text per se. At the beginning of each of the -longer sections we summarize the relevant studies; we encourage readers who want more details on that variable to read the section further. We follow the summary with a hypothesized relationship of the ecological variable to territoriality. Whereas these hypotheses fit most reports, they are perhaps most useful as possibilities to be examined in future research.

Food quantity.--Twelve papers (Young, 1956 [C]; Davies and Snow, 1965 [C]; Smith, 1968 [C]; Zahavi, 1971 [E]; Rowley, 1973 [C]; Craig, 1979 [C]; Peterson, 1979 [C]; Myers et al., 1981 [C]; Ferguson et al., 1983 [E]; Ostfeld, 1986 [P, E]; Carpenter, 1987 [C, E]; Ims, 1987 [C]) reported territoriality decreased as amount of food increased, and two papers (Fricke, 1977 [C]; Carpenter, 1987 [C, E]) reported that limited food increased territoriality. However, four papers (Miller, 1974 [C]; Gill and Wolf, 1975 [C, El; Carpenter and MacMillen, 1976 [P, C, E]; Carranza et al., 1990 [C]) found that abundant food increased territoriality, whereas ten papers (Snow, 1956 [C]; Prior, 1968 [C]; Walsberg, 1977 [C]; Kodric-Brown and Brown, 1978 [C]; Gass and Lertzman, 1980 [C]; Lederer, 1981 [C]; Caro and Collins, 1986 [C]; Hannon et al., 1987 [C]; Kruuk and Parish, 1987 [C]; Maher, 1994 [C]) reported that limited food was associated with a lack of territoriality. Davies and Houston (1983 [C]) and Wyman and Hotaling (1988 [E]) reported both findings: increased food produced territoriality and further increases in food quantities terminated territoriality. We also found reports of both abundance and scarcity having no effect on territoriality (Armstrong, 1992 [P, E]; Hofer and East, 1993 [C]; McFarland, 1994 [E]). We conclude the relationship of food quantity to territoriality is not linear, and, contrary to Grant's (1993) hypothesis, food is sometimes too abundant in nature for territories to be maintained.

The relationship of food quantity to territoriality often is modeled as an inverted U function (e.g., Brown, 1964 [P]; Gill and Wolf, 1975 [C, E]; Carpenter and MacMillen, 1976 [P, C, E]; Davies and Houston, 1983 [C]; Wyman and Hotaling, 1988 [E]; Grant, 1993; Fig. 1A). This model proposes that when food quantities are very low, costs of defending resources exceed the benefits because energy spent defending resources would be greater than energy gained and/or because competitors are so rare that the small amount of resources lost to them does not justify defense. The cost-benefit ratio shifts toward territoriality as the level of food increases, and it eventually reaches a point at which territoriality is cost effective. If food becomes very abundant, territoriality ceases to be beneficial because the amount of food exceeds the intruders, so competition ceases, and/or because competitors are so numerous (perhaps measured as rate of intrusions per unit time) that excluding them all would take more energy than defense of the resource warrants.

Thus, the relationship of territoriality to food quantity can be conceptualized as a simple dependent variable--independent variable function. Ideally, the dependent variable would be territorial behavior, measured operationally in units such as latency to approach intruders (see the last section). In practice, the dependent variable has been the benefits minus costs of territoriality plotted as a function of the level of the independent variable (food quantity; Gill and Wolf, 1975 [C, E]; Davies and Houston, 1983 [C]; Wyman and Hotaling, 1988 [E]). This approach tests the hypothesis that behavior is optimal, provided assumptions about cost-benefit calculations are correct. Alternatively, one can test the hypothesis that the cost-benefit calculations are correct, provided one assumes behavior is optimal. However, since behavior is recorded as changing only at the threshold points (the transition between benefits exceeding costs and vice versa), territoriality can be plotted only as an off-on, either-or funct ion, not as a quantity or matter of degree. This limitation is compatible with the perspective that territoriality is not graded, but, rather, an animal either is or is not territorial (Fig. 1A). The cost-benefit ratio plotted in an optimality approach has come to serve as a surrogate for behavior, e.g., Wyman and Hotaling (1988 [E]) label that y-axis "Territorial Tendency." Food quantity data from these studies can be plotted on the inverted U function. Simply place one level of food quantity in the area where benefits of territoriality exceed costs, and place the other point where they do not, By placing the value at which the subject was territorial in the midrange of values and the other outside the midrange, we have arranged the data to conform to the inverted U hypothesis.

However, we must acknowledge that our placement with respect to the horizontal axis is rather arbitrary because amount of food often is quantified only at two points on an ordinal scale: "more" and "less." Since all but two studies were unidirectional (territoriality at one level and its absence at another), we also could have plotted nearly all the studies as a mirror image. With the studies thus arranged, the function would be a U function (Fig. 1B). However, given good theoretical reasons to expect an inverted U function, and the two studies that reported that function (Davies and Houston, 1983 [C]; Wyman and Hotaling, 1988 [E]), the inverted U function is a useful hypothesis for the relationship between food quantity and territoriality.

Whereas using cost-benefit ratio as a dependent variable is valuable, plotting behavior directly could reveal trends toward or away from defense and so reduce ambiguity Also, by eliminating the requirement that behavior crosses a threshold between categories of spacing systems, we could benefit from studies that now get "negative" results and go unreported. We further discuss the importance of quantifying behavior in the last section.

Food distribution.--Some authors stated that clumped food distribution leads to territoriality (Davies, 1976 [C]; Woodward, 1979 [C]; Vaughan and Schwartz, 1980 [C]; Lederer, 1981 [C]); but, in other cases food was clumped or patchy, yet animals were not territorial (Evans, 1951 [C]; Bailey, 1974 [P, C]; Desrochers and Hannon, 1989 [P, C]; Tsukada, 1997 [C]). Krebs (1974 [C]) found that more dispersed food produced territoriality.

Only two studies experimentally manipulated food distribution alone. Evenly distributed food resulted in grouping, whereas territorial behavior was observed when food was distributed in piles (Zahavi, 1971 [E]). Similarly, when food was more spatially clumped animals monopolized the resource more readily (Grant and Guha, 1993 [E]). These observations support correlational data that clumped food distribution leads to territoriality, suggesting that unrecorded variables may have overridden the effect of distribution in some correlated studies.

Craig and Douglas (1986 [C]) proposed a continuum to explain the correlation between food distribution and spacing system; at one end, when resources were extremely clumped, animals were organized in absolute social hierarchies due to higher costs of aggression. Higher intruder pressure made defense uneconomical. Conversely, when resources were more spatially dispersed animals were more territorial, and when food was concentrated in small patches some animals could maintain exclusive access to that food. The hypothesis most compatible with these data is an inverted U shaped model of the effect of food distribution: highly clumped or evenly distributed resources are not defended, but moderately clumped resources are defended.

Food predictability.--Four papers (Walsberg, 1977 [C]; Woodward, 1979 [C]; Grand and Grant, 1994 [E]; Bryant and Grant, 1995 [E]) reported that territoriality or resource monopolization was correlated with a spatially or temporally predictable food base. The hypothesis that best conforms to these data is a linear relationship between food predictability and net benefits of territoriality (Fig. 2). However, food caching species may behave contrary to this rule. Tye (1986 [E]) demonstrated that temporally unpredictable food led to territoriality in fieldfares (Turdus pilaris). He suggested that territoriality was an adaptation by which these birds could store their food supplies (apples) against periods of scarcity.

Food type.--Whereas several authors discussed food type, few discussed the same categories in similar ways, and all evidence was correlational. When resources can be defended, presumably due to characteristics such as quantity, distribution or predictability, animals maintain territories that include those food items.

Brook charr (Salvelinus fontinalis) feeding on drift in fast water were territorial, yet when they fed on benthic organisms in slow water, they were not territorial (Grant and Noakes, 1987 [C]). Brady (1979 [C] cited in Moehlman, 1989) observed that crab eating foxes (Cerdocyon thous) were territorial when eating crabs and vertebrates, but they foraged in overlapping home ranges when eating fruit and insects. Pitelka et al. (1955 [C]) and Andersson and Gotmark (1980 [C]) reported that jaegers (Stercorarius spp.) feeding on abundant lemmings were territorial, but jaegers feeding on fish via Kleptoparasitism were not. The "victims" of kleptoparasitism could not be defended, but a patch of ground with its resident lemmings was defensible; thus, food type relates to underlying food distribution patterns.

Population density.--In most empirical reports territoriality was more likely as population density decreased (Davis, 1958 [E]; Zezulak and Schwab, 1979 [C]; Liberg, 1980 [C]; Ims, 1987 [C]; Langbein and Thirgood, 1989 [C]; Nelson, 1995 [C, E]; Adler et al., 1997 [C]). Lockie (1966 [C]) reported that moderate population density correlated with territoriality, whereas Ferron and Ouellet (1989 [C]) found that low and intermediate densities were correlated with territoriality.

Davis (1958 [E]), Cole and Noakes (1980 [E]) and Magurran and Seghers (1991 [E]) demonstrated that territoriality ceases at high density. This relationship also was reported by Kawanabe (1969 [C]), Prieto and Ryan (1978 [P, C]), Jarman (1979 [C]) and Ferron and Ouellet (1989 [C]). The best experimental evidence is presented by Cole and Noakes (1980 [E]) and Magurran and Seghers (1991 [E]). They showed that, when other things are equal, increased population density can end territoriality because of increased rates of interaction (intruder pressure).

A few studies reported apparently contradictory results. Turpie (1995 [C]) reported that territoriality occurred when density exceeded a threshold value. Lockie (1966 [C]), Kitchen and O'Gara (1982 [C]), Rothstein et al. (1984 [C]), Maher (1994 [C]) and Byers (1997 [C]) reported low density was not compatible with territoriality.

These apparent contradictions have several possible explanations. One possibility is that the terms "high" and "low" signify different things to different investigators. Another possibility is that population density accounts for little of the variance in degree of territoriality and unobserved variables actually determined the outcomes. Yet another possible explanation is that densities used in laboratory settings were not representative of densities seen in natural circumstances. Langbein and Thirgood (1989 [C]) admit to the somewhat artificial nature of the parks in which they conducted studies on fallow deer (Dama dama) and Cole and Noakes (1980 [E]) cite a lack of information about fish densities in the wild for comparison with densities used in the laboratory. Perhaps population density can be too low to support territoriality, due to low benefits, as well as too high. If we regard these contradictions as signal rather than noise, they prove compatible with the hypothesis of an inverted U function. The evidence for this hypothesis certainly is strong enough to justify systematic testing.

Habitat.--Structural complexity and water current are two habitat features most commonly asserted as determinants of territoriality. Predictions about the effect of structural complexity on territoriality are contradictory. Bronson (1979 [P]) predicted "reasonable" structural complexity will support territoriality as long as food is abundant and predictable. Walther (1972 [C]) and Gibson and Bradbury (1987 [C]) agreed that complex habitats correlate with territoriality due to availability of landmarks by which animals can demarcate boundaries. Kolb (1986 [P]), however, predicted territoriality is more likely in a less structured habitat because boundaries are easier to demarcate. Although Kolb did not observe territoriality in his study of red foxes ( Vulpes vulpes), Basquill and Grant (1998 [E]) found that zebra fish (Danjo rerio) were more aggressive and showed higher monopolization of food in a simple vs. complex habitat. Species differences could be important here, in that different species rely on diffe rent types of marking to delineate boundaries (e.g., dung piles or behavioral displays vs. glandular secretions on vegetation). Structural complexity is likely to affect important features of an individual's biology, such as predator avoidance and foraging energetics. Consequently, it should be studied further, and it may reveal the importance of other determinants that covary with structural complexity, such as population density or food distribution.

Several studies have examined the effect of water current on territoriality in stream fishes, but all these studies have been conducted on salmonids which feed on materials drifting from upstream. Researchers have consistently found that such fish are more territorial in flowing water than in still water (Newman, 1956 [C]; Kalleberg, 1958 [E]; Cole and Noaltes, 1980 [C]; Biro et al., 1997 [C]).

Space.--Reports of the effect of space availability are contradictory, despite the high quality of the evidence. Anderson (1961 [P, C]), Poole and Morgan (1976 [E]), Karstad and Hudson (1986 [C]), Kodric-Brown (1988 [E]) and Strahl and Schmitz (1990 [C]) all reported that confinement reduces territoriality. However, Greenberg (1947 [E]) and Itzkowitz (1977 [E]) demonstrated experimentally that decreasing space produced territoriality. Itzkowitz also found that increasing the amount of space increased the amount of territoriality; however, responses also depended on presence or absence of females, suggesting changes in the cost-benefit ratio and, therefore, economic defensibility of space.

Apparent contradictions in these experimental findings may be explained by the different sized habitats used in the experiments. Whereas Itzkowitz (1977 [E]) and Kodric-Brown (1988 [El) both experimented with pupfishes (Cyprinodon spp.), Itzkowitz's manipulations of space involved small tanks measuring 0.072 [m.sup.3] or 0.036[m.sup.3]. Kodric-Brown used much larger aquaria, measuring 4.41 [m.sup.3] and 1.09 [m.sup.3], which mimicked wild habitats. Likewise, Greenberg's experiments with sunfish (Lepomis cyanellus) used small spaces; the largest was 0.151 [m.sup.3]. Thus, researchers' "large" spaces are not comparable to each other because one study's "large" space is another study's "(very) small" space.

Differing results could be consistent with an inverted U model of the effect of space on territoriality: moderate amounts of space support territoriality, but, because they are not economically defensible, small and large amounts do not. However, no single study spans a broad enough range of space to produce both onset and termination of territoriality. Moreover, in the two pupfish studies, the largest space in one study is smaller than the smallest space in the other. Consequently, territoriality is reported at the highest and lowest levels, but it is eliminated when intermediate amounts of space are available. This would plot as a U function. Clearly this relationship needs systematic study.

Determination by combinations of ecological variables.--Many authors predicted or reported data indicating that territoriality resulted from two or more variables acting in combination. In the real world several determinants will usually, perhaps always, operate simultaneously. Whereas we commend steps in this direction, the methodology of these studies does not allow us to partition the contribution of each separate variable.

The analysis would be more illuminating with a multiple regression technique. Since that approach rarely has been used in territorial studies multideterminant studies offer considerable insight into the investigator's reasoning, but not necessarily as much information about how territoriality is determined. However, a pattern may be revealed when several studies of multiple determinants have some, but not all, variables in common, e.g., in studies combining food predictability with another variable.

Combinations of food variables.--All authors who discussed food quantity and distribution together had consistent findings, although most evidence was correlational. Konecny (1987 [C]) observed that limited but patchy food led to less exclusive home ranges, i.e., more territoriality. Carranza et al. (1995 [E]) created patches of scarce food which allowed females to concentrate in specific areas, and males then established territories. Other studies also found that when food was abundant and patchily distributed animals were not territorial (Magnuson, 1962 [El; Richard, 1974 [C]; Rogers, 1987 [P, C]).

Bronson (1979 [P]) predicted that if food was both abundant and predictable animals would be territorial. Kavanagh (1981 [C]) reported that limited but predictable food sources were defended. Both authors discussing food quantity and predictability agreed with each other on the effects of predictability.

One paper (Liberg and Sandell, 1989 [P, C]) predicted that the combination of predictable evenly distributed food would lead to territoriality, and two papers (Sundquist, 1981 [C]; Heligren and Vaughn, 1990 [C]) reported this relationship. Zahavi (1971, [El) and Krebs (1974 [C]) described an allied finding that large, unpredictable, clumped food sources precluded territoriality; Davies and Hartley (1996 [E]) also found increased territory overlap (but territories were not abandoned) when food was patchy and unpredictable. Finally, Rubenstein (1981b [E]) demonstrated experimentally that predictable clumped distributions of food produced territoriality.

Predictability, when combined with patchy food distribution, may account for most of the variance in the data. This also may explain findings reported under food distribution alone; powerful in behaviorally flexible species since it could operate via learning, and unpredictability might produce extinction.`

Only two papers attempted to address the combination of food distribution, quantity and predictability. Rogers (1987 EP, C]) reported that if abundant and patchy food was unpredictable it would lead to increased home range overlap, terminating territoriality. Bennett (1986 [C]) reported the related finding that when food was abundant and evenly distributed but unpredictable animals were not territorial. The difference between the studies is food predictability, again suggesting it may be more important as a determinant than other variables.`

Combinations of population density and other variable.--Rolando et al (1995 [C]) reported that high food quantity and population density did not produce territoriality and Middendorf (1979 [P, E]) demonstrated that at high population density, even with supplemental food, animals were not territorial, but at intermediate population densities some animals were territorial. He concluded population density was a more important determinant of spatial organization than was food quantity.

When food was clumped males maintained exclusive areas regardless of population density. However, when food was randomly distributed in space males at high and low densities did not maintain territories. Only males exposed to intermediate population densities continued to maintain territories (Rubenstein, 1981b [E]). This lends support to the hypothesis that the relationship between population density and territoriality is not linear.`

Two papers investigated the combination of population density and amount of space. In small areas with low population densities animals were not territorial, but they switched to territoriality when density was high because of increased competition for breeding sites (Kodric-Brown, 1988 [E]). Itzkowitz (1977 liE]) also found that in larger areas, as density increased, territoriality increased. He concluded that total area was just as important in determining spatial organization as was population density.`

Mate distribution and abundance.--A pattern of abundant, evenly distributed females was predicted to lead to male territoriality (Liberg and Sandell, 1988 EP, C]). Liberg (1984 [C]) reported that a less concentrated and predictable female distribution correlated with partial territoriality in males; males could not exclude all competitors. However, Ims (1987 [C]) reported that clumped and abundant (because of synchronous breeding) females, along with low male density, promoted male territoriality. Carranza et al. (1996 [C]) reported similar findings. Yet, Nelson (1995 [C, E]) found that the pattern of female distribution in space had no effect on territoriality in males. Although males were more territorial at higher densities of females, after he corrected for the relationship between home range size and exclusivity, he found that mate density did not affect territoriality directly.


The foregoing review demonstrates that territoriality can be affected by many different ecological variables. The review also shows that the more times a single variable, e.g, food quantity, has been tested as a determinant of territoriality, the more likely apparently contradictory studies occur in the literature. However, many of these apparent contradictions appear to be esolvable.

Only food predictability is linearly correlated with territoriality; the relationship between several other variables and territoriality appears to have an inverted U shape. This pattern already has been proposed for food quantity, i.e., very abundant food and very scarce food would not be defended, but intermediate levels would be defended (Gill and Wolf, 1975 [C, E]; Carpenter and MacMillen, 1976 [P, C, E]; Wyman and Hotaling, 1988 [El) and the same model can be applied to other variables such as population density or food distribution. Grant's (1993) analysis of fish studies concluded that resource density theoretically has an inverted U effect on territoriality, but he suggested the upper threshold will seldom, if ever, be reached in nature. Our review of all instances of intraspecific variation in all vertebrate classes suggests that results from studies of food quantity, food distribution, population density and perhaps spatial variation strongly hint that an upper threshold frequently is reached. Like Grant (1993), we note that the variable with the most consistent effect-predictability--seems unlikely to be subject to nonlinear effects. We caution that weakly quantified data readily can be molded to the reviewer's model and, in analyses of a multi-determined phenomenon like territoriality, the influence of any single studied variable may be overridden by the influence of one or more unrecorded variables. Consequently, some reported effects, e.g, of food quantity on territoriality, may fit our hypothesized inverted U function because they can be placed somewhat arbitrarily. Still, we conclude that the evidence strongly suggests that an inverted U function explains much of the data.


Most reports assert that the ecological variable induces territoriality directly rather than indirectly by altering an intervening variable that then acts as a determinant. However, in some cases, authors propose a two or more step process or causal pathway. Most causal pathways we report were described in empirical papers, but the pathways themselves were not examined in the study. Rather, they were post hoc explanations of the observations. Path analysis provides a method for testing hypotheses about causal pathways (Mitchell, 1993). We are not aware, however, that it has been employed in studies of ecological determinants of territoriality. Although the validity of the proposed pathways cannot be evaluated, they may offer a useful starting point in the search for proximate mechanisms by which ecological variables determine territoriality. Therefore, we summarize them below.

Intruder pressure was the most frequently proposed intervening variable. The pattern for its operation was that a change in quantity of some resource would alter intruder pressure in a way that facilitated territoriality. Desrochers and Hannon (1989 [P, C]) suggested that clumped distribution of high quality food would increase intruder pressure and territoriality would decrease in response to increased intruder pressure. Several authors proposed that increased quantity or density of food would decrease territoriality in the same way (Young, 1956 [C]; Davies and Snow, 1965 [C]; Rowley, 1973 [C]; Craig, 1979 [C]; Myers et al., 1979a [C], 1981 [C]) and Davies and Houston (1983 [C]) attributed acceptance of satellites into territories as a response to higher intruder pressure created by increased food. Ims (1987 [C]) proposed a similar pathway with mates as the resource; spatially clumped females induce reproductive synchrony among themselves which then reduces male density and intruder pressure and enhances te rritoriality among males.

This view conflicts somewhat with the proposal that scarce (rather than abundant) food increases intruder pressure and so decreases territoriality (Ewald and Carpenter, 1978 [F]; Kodric-Brown and Brown, 1978 [C]; Tye, 1986 [F]). Moreover, Ewald and Carpenter (1978 [E]) demonstrated experimentally that increased intruder pressure (attributed to less food) reduced territoriality. In contrast, Tye (1986 [F]) demonstrated that smaller amounts of food increased intruder pressure and led to territoriality; in his view, this pattern of food availability created a smaller area from which to exclude competitors compared to areas containing larger amounts of food. A U shaped model of the relationship between food quantity and territoriality again could accommodate these apparent contradictions. Furthermore, the spatial scale over which food increases will be important. Resources concentrated over a larger regional area may attract more intruders than those distributed in a smaller local area (Carpenter, 1987 [C, El).

Rubenstein (1981a [C]) proposed female group stability as an intervening variable leading to a spacing system. He suggested foraging conditions that precluded permanent groups of females (low quality, widely scattered, patchy vegetation) would support male territoriality because males could not defend those females, whereas conditions supporting stable female groups (larger, more evenly distributed patches of high quality food) would not produce territoriality among males; males would defend groups of females and move freely with them rather than defend a fixed location.

Mate dispersion also was proposed as an intervening variable. Langbein and Thirgood (1989 [C]) suggested open habitat decreased male territoriality because it led to greater female cohesion, making defense of female groups more feasible, whereas Cowan and Bell (1986 [C]) suggested burrow availability could produce male territoriality by causing females to group. Low amounts of food can lead to fewer numbers of females in an area, causing males to abandon territories (Caro and Collins, 1986 [C]). Similarly, higher food productivity or patchy distribution of food could attract females to areas, then males establish territories there (Carranza et al, 1990 [C], 1996 [C]). Few studies have attempted to demonstrate this relationship experimentally, but addition of supplemental food induced females to aggregate in particular areas, which males then defended as territories (Carranza et al., 1995 [E]).


Our review suggests that progress can proceed more rapidly by increased use of three tools: (1) quantification of ecological variables, (2) quantification of social systems (via quantification of behavior) and (3) use of multiple regression and path analysis to explore the relationship of these two sets of variables. The first and third tools are established and we discuss them only briefly. Quantification of social systems, however, is not well developed, so we discuss it further.

Researchers have perfected measurement and manipulation of many ecological variables, e.g., we can precisely determine plant or prey density and chemical composition. Food quantity is perhaps the most frequently quantified variable. Gill and Wolf (1975) and Lott and Lott (1992) measured [mu]l of nectar in flowers, the food resource for sunbirds. Myers et al. (1979a) quantified both density of invertebrates that territorial sanderlings (Calidris alba) ate and intruder density. Kitchen (1974) quantified food quantity by measuring fresh and dry weights available to pronghorns. Water velocity has been quantified in studies of stream fishes (Grant and Noakes, 1987; Lott and North, 1998).

The way experiments are performed, i.e., on a regional or local scale, affects results and the possibility of a shift in the observed spacing system (Carpenter, 1987; Armstrong, 1992). Manipulations should be performed over relevant time periods and in dimensions appropriate to the species. Indeed, negative results could be an artifact of a limited time scale; most studies are conducted over a period of days or weeks. Furthermore, the entire region relative to localized feeding areas may need to be considered, as in the case of nectarivorous birds (Carpenter, 1987).

Multiple regression techniques also are well established. Several studies of territoriality used multivariate procedures (multivariate analysis of variance: Cole and Noakes, 1980; factor analysis: Ims, 1987; discriminant analysis: Langbein and Thirgood, 1989; Middendorf, 1979; multiple regression and partial correlation: Myers et al, 1981). Of the available techniques, multiple regression is often best suited for explaining the determination of one or a few dependent variables (e.g., the amount of one or a few indices of territoriality) by the combined effect of several independent variables (Kerlinger and Pedhazur, 1973). Multiple regression techniques may give the field worker a level of rigor in analysis comparable to that achieved in laboratory experiments without losing the complexity of the natural environment (Brown et al., 1978; Ims, 1987; Langbein and Thirgood, 1989), plus they can calculate the amount of variation accounted for by each variable and the direction of its effects (Draper and Smith, 19 81; Ludwig and Reynolds, 1988; Phillipi, 1993).

To adopt a multiple regression approach one must identify several variables to measure, clearly define those variables and measure them quantitatively. These measurements could be conducted for territorial and nonterritorial individuals, for territorial and nonterritorial populations or for members of the same population at different times such as before and after an experimental manipulation. Our search of the literature yielded 20 ecological variables that at least sometimes act as determinants (Table 1). This listing is probably not exhaustive, but it presumably includes most of the important determinants. Therefore, it provides a good starting point for investigators seeking likely candidates. Our tabulation of the variables examined in different taxa also can provide help in searching for variables likely to operate in a particular taxon (Tables 2-6).

Since most ecological variables (e.g. food quantity, population density) are probably not related linearly to territoriality, they would not meet the linearity assumption of multiple regression. However, variables can be transformed, e.g. logistically or as quadratic terms, so the relationship is linear (Ludwig and Reynolds, 1988).


Researchers have not developed methods to quanti1 social systems to the same degree that they have developed methodology to quantify ecological variables. Yet recently, several investigators have used different behavioral characteristics to quantify territorial behavior patterns. For example, Pyke et al. (1996) urged that the spacing system we call territoriality be defined as a complex of several quantified behavioral attributes including (1) intensity of territorial behavior, (2) sharpness of territorial boundary and (3) exclusivity of resource use. Pyke et at. chose these variables as particularly suitable for studies of territoriality in honeyeaters and they would use the resulting quantitative summary to classify the spacing system as territorial or not territorial. In a field experiment on another nectarivore, the bronzy sunbird (Nectarinia kilimensis), Lott and Lott (1992) chose a different set of variables: (1) percent time absent, (2) unchallenged intruders per hour present, (3) challenged intruders per hour present and (4) latency to displacement of challenged intruders. Wyman and Hotaling (1988), studying cichlid fishes (Etroplus maculatus and Pelmatochromis subocellatus kribensis) recorded (1) charges, (2) rams, (3) territories defended and (4) lateral displays. Lott and North (1998) measured (1) site specificity of aggression, (2) site fidelity and (3) exclusivity of space use in rainbow trout (Oncorhyncus mykiss). The several quantities generated by such an approach can be arithmetically summarized into a single value (see Lott and North, 1998). This value then can represent the aggregate degree of territoriality and can be plotted as a function of food quantity or other relevant variable. This would test directly the predictive power of optimality hypotheses.

Such measures also allow us to examine our preconceptions about territoriality. For example, do all measures always have the same relationship to one another, thus suggesting that territoriality always takes the same form? Perhaps animals actually pursue a set of somewhat independent strategies, e.g., remaining site faithful under many circumstances, but only challenging intruders under some of them; only threatening under some circumstances and both threatening and attacking under others; or maintaining sharp boundaries under some circumstances and only threatening, whereas maintaining soft boundaries under other circumstances, but both threatening and attacking. Such analyses offer the possibility of greater insight into spatial strategies.

A quantified description of territoriality also can be related to a quantified alternative social system. Bromley (1977) measured the degree to which the outcome of a dominance interaction is a function of the location where it occurs. Lott and North (1998) developed a method for quantitatively describing the degree to which (1) a spatial strategy (territoriality) and (2)

a relational strategy (dominance) may contribute to a single social system value. They discovered that individuals could not be placed into discrete categories of dominance and territoriality; instead, individuals displayed components of both types of social systems. By quantifying behavior patterns and assigning numerical scores to individuals, Lott and North detected more subtle differences in individual behavior and social organization as ecological conditions changed. Minta (1990) has taken this approach a step further by creating a three dimensional model that allows a quantitative summary of the joint contribution of territoriality, d ominance and temporal avoidance strategies to a three dimensional (three strategy) social system.

Treating territoriality and (or) its behavioral components as quantities also would allow us to benefit more from studies currently regarded as yielding negative results. A change in food quantity may cause a shift along a continuum of spatial behavior in one direction or the other (e.g. toward completely overlapping home ranges or toward exclusive home ranges); however, the change may not be great enough to change the category to which the social organization is assigned, i.e., to undefended home range or to territory.

Different quantitative indices of territoriality could be used as separate behavioral indices of territoriality in a multivariate procedure (e.g., Ims [1987] used factor analysis to categorize behavior in animals' own home ranges and in home ranges of other individuals). They also could be combined into a single index to be regressed against a set of ecological variables.

We noted earlier that several authors hypothesized causal pathways by which ecological variable A determines ecological variable B, which, in turn, determines the degree of territoriality. Verbal models of such hypotheses are not testable, but path analysis (Mitchell, 1993) provides a quantitative, statistical method for modeling such hypotheses and rigorously testing them. Consequently, it provides a useful means to understand how ecological variables determine territoriality. Path analysis has weaknesses similar to multiple regression, e.g., effects of the variables should be linear and all important variables should be identified (Mitchell, 1993), and this method works best when variables are manipulated experimentally (Smith et al., 1997).

Stephens and Dunbar (1993) have applied another technique, dimensional analysis, to the question of territory size, and their model illustrates the potential power of this approach in behavioral ecology. As currently developed, the model only predicts whether or not an animal should be territorial as a function of the size of the space available to defend, and it treats territoriality as a categorical variable (i.e., animals are either territorial or they are not) rather than a quantitative one. Consequently, its use in answering the questions we raise is not yet clear. However, dimensional analysis clearly facilitates comparisons and quantitative analysis of ecological variables.

Thus far, the study of ecological determinants of territoriality has been conceptually rich but not always rigorous enough to draw robust conclusions. Future progress in our understanding not only of which determinants influence territoriality, but how they influence behavior patterns at a proximate level, could be accelerated by quantifying both the independent (ecological) variables and the dependent (behavioral) variables and by making more use of multivariate techniques.

Acknowledgments.--We thank G. Barlow, R. Bowen, M. Daly, J. W. A. Grant, D. Hu, L. Isbell, B. Jakob, S. Minta, C. Pennuto, N. Solomon, J. Stamps, D. Van Vuren and three anonymous reviewers for the time and effort they spent reviewing earlier versions of this manuscript. This research was partially supported by the Department of Wildlife and Fisheries Biology Hatch Fund No. 3915 and the University of Southern Maine.

(1.) Corresponding author: Telephone (207)780-4612; FAX (207)228-8288; e-mail:


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    Ecological variables, listed by category, influencing territoriality
              and the number of papers discussing that variable
                            Category of relationship
Variable                           Predicated        Correlated
  Quantity                            11                36
  Distribution                        11                27
  Predictability                       4                16
  Quality                              1                 4
  Renewal rate                         2                 2
  Type                                 0                 6
  Density                              0                 2
  Assessibility                        0                 0
  Distribution                         0                 6
  Quantity                             0                 1
  Predictability                       0                 1
  Quality                              0                 1
Population density                     2                19
Habitat features                       6                12
Mates                                  2                 3
Space                                  1                 2
Refuges/spawning/home sites            1                 5
Predation pressure                     0                 3
Host nests                             1                 2
Energy availability                    0                 0
Variable                     demonstrated
  Quantity                       12
  Distribution                   10
  Predictability                  6
  Quality                         1
  Renewal rate                    1
  Type                            0
  Density                         0
  Assessibility                   1
  Distribution                    1
  Quantity                        0
  Predictability                  0
  Quality                         0
Population density                9
Habitat features                  3
Mates                             6
Space                             5
Refuges/spawning/home sites       1
Predation pressure                0
Host nests                        0
Energy availability               1

Ecological variables listed by species of fish. Abbreviations used: [P] = predicted relationship; [C] correlated relationship; [E] experimentally demonstrated relationship; AS = assessibility; DE = density; DS = distribution; EA = energy availability; HB habitat features; HN host nests; MA = mates; PD predation pressure; PO = population density; PR predictability; QL quality; QN = quantity; RE = renewal rate; RF = refuges, home/shelter or spawning sites; SP space; TY = type
       Species                               Reference               Food
Oncorhyncus mykiss                    Newman, 1956 [C]
                                      Jenkins, 1969 [E]              QN
                                      Cole and Noakes, 1980 [C, E]
Salmo trutta                          Kalleberg, 1958 [C]
                                      Jenkins, 1969 [E]              QN
Salmo solar                           Kalleberg, 1958 [C]
Salvelinus fontinalis                 Newman, 1956 [C]
                                      Grant and Noakes, 1987 [C]     TV
                                      Biro et al., 1997 [C]
Plecoglossus altivelis                Kawanabe, 1969 [C]
Brachydanio (=Danio) rerio            Grant and Kramer, 1992 [P, E]  RE
                                      Basquill and Grant, 1998 [E]
Theragra chalcogramma                 Ryer and Olla, 1995 [E]        DS
Oryzias latipes                       Magnuson, 1962 [E]             DS, QN
                                      Bryant and Grant, 1995 [E]     PR
Cyprinodon pecosensis                 Kodric-Brown, 1988 [E]
Cyprinodon variegatus                 Itzkowitz, 1977 [E]
Poecilia reticulata                   Magurran and Seghers, 1991 [E]
Elassoma evergladeii                  Rubenstein, 1981b [E]          DS, PR
Lepomis cyanellus                     Greenberg, 1947 [E]
Cichlasoma nigrofasciatum             Grant and Guha, 1993 [E]       DS
                                      Grand and Grant, 1994 [E]      PR
Etroplus maculatus                    Wyman and Hotaling, 1988 [F]   QN
Pelmatochromis subocellatus kribensis Wyman and Hotaling, 1988 [E]   QN
Dascyllus trimaculatus                Fricke, 1977 [C]               QN
Pomacentrus albicaudatus              Fricke, 1977 [C]               QN
Halichoeres garnoti                   Robertson, 1981 [C]
Thalassoma bifasciatum                Fitch and Shapiro, 1990 [C]    TV
Xyrichtys splendens                   Nemtzov, 1997 [C, E]
Scarus croicensis                     Barlow, 1975 [C]               DS, PR
Scarus iserti                         Dubin, 1981 [C]
Scarus taeniopterus                   Barlow, 1975 [C]               DS, PR
                                      Dubin, 1981 [C]
Sparisoma aurofrenatum                Barlow, 1975 [C]               DS, PR
                                      Dubin, 1981 [C]
Sparisoma viride                      Barlow, 1975 [C]               DS, PR
       Species                        Other
Oncorhyncus mykiss                    HB
                                      P0, HB
Salmo trutta                          HB
Salmo solar                           HB
Salvelinus fontinalis                 HB
Plecoglossus altivelis                P0
Brachydanio (=Danio) rerio
Theragra chalcogramma                 SP
Oryzias latipes                       P0
Cyprinodon pecosensis                 P0, SP
Cyprinodon variegatus                 P0, SP
Poecilia reticulata                   PO
Elassoma evergladeii                  P0
Lepomis cyanellus                     SP
Cichlasoma nigrofasciatum
Etroplus maculatus
Pelmatochromis subocellatus kribensis
Dascyllus trimaculatus                RF
Pomacentrus albicaudatus              RF
Halichoeres garnoti                   RF
Thalassoma bifasciatum                HB
Xyrichtys splendens                   RF,HB
Scarus croicensis                     P0
Scarus iserti                         RF
Scarus taeniopterus                   P0
Sparisoma aurofrenatum                P0
Sparisoma viride                      P0
                  Ecological variables listed by species
                        of amphibian and reptiles.
                     Abbreviations as shown in Table 2
       Species                  Reference              Food   Resources Other
Plethodon vehiculum       Ovaska, 1988 [P]             DS               HB
Family Iguanidae          Case, 1978 [P, C]                             PD
Anolis aeneus             Stamps, 1973 [P]             DS, QN
Urosaurus ornatus         M'Closkey et al., 1987 [E]                    MA
Sceloporus jarrovi        Middendorf, 1979 [P, E]      QN               PO
Sceloporus undulatus      Ferguson et al., 1983 [E]    QN
Ctenosaura hemilopha      Brattstrom, 1974 [E]                   DS
Ctenosaura pectinata      Evans, 1951 [C]              DS
Sauromalus obesus tumidus Prieto and Ryan, 1978 [P, C] QN               PO
             Ecological variables listed by species of birds.
                     Abbreviations as shown in Table 2
Species                      Reference
CLASS AVES                   Lott, 1991 [P]
Melanerpes formicivorus      Hannon et al., 1987 [C]
Centrocercus urophasianus    Gibson and Bradbury, 1987 [C]
Ardea herodias               Krebs, 1974 [C]
Porphyrio p. melanotus       Craig, 1979 [C]
Selasphorus rufus            Kodric-Brown and Brown, 1978 [C]
                             Gass and Lertzman, 1980 [C]
Calypte anna                 Ewald and Carpenter, 1978 [E]
Family Anatidae              Nudds and Ankney, 1982 [C]
Family Scolopacidae          Myers et al., 1979b [C]
Tryngites subruficollis      Myers, 1980 [P, C]
Calidris alba                Myers et al., 1979a [C]
                             Myers et al., 1981 [C]
Pluvialis squatarola         Turpie, 1995 [C]
Catoptrophorus semipalmatus  McNeil and Rompre, 1995 [C]
Catharcta maccormicki        Pietz, 1987 [C]
Catharcta lonnbergi          Pietz, 1987 [C]
Stercorarius spp.            Pitelka et al., 1955 [C]
                             Andersson and Gotmark, 1980 [C]
Opisthocomus hoazin          Strahl and Schmitz, 1990 [C]
Corvus spp.                  Rowley, 1973 [C]
Garrulus glandarius          Rolando et al., 1995 [C]
Anthornis melanura           Craig and Douglas, 1986 [C]
Phainopepla nitens           Walsberg, 1977 [C]
Parus atricapillus           Smith and Van Buskirk, 1988 [P]
                             Desrochers and Hannon, 1989 [P, C]
Nectarinia reichenowi        Gill and Wolf, 1975 [C, E]
Vestiaria coccinea           Carpenter and MacMillen, 1976 [P,
                              C, E]
                             Carpenter, 1987 [C, E]
Phylidonyris nigra           Armstrong, 1992 [P, E]
Phylidonyris novaehollandiae Armstrong, 1992 [P, E]
                             McFarland, 1994 [E]
Motacilla alba yarrelli      Davies, 1976 [C]
Motacilla alba               Davies and Houston, 1983 [C]
Motacilla alba alba          Zahavi, 1971 [E]
Prunella modularis           Davies and Hartley, 1996 [E]
Turdus migratorius           Young, 1956 [C]
Turdus merula                Snow, 1956 [C]
Turdus philomelos            Davies and Snow, 1965 [C]
Turdus pilaris               Tye, 1986 [E]
Myadestes townsendi          Lederer, 1981 [C]
Tiaris olivacea              Pulliam et al., 1972 [C]
Molothrus ater               Elliott, 1980 [C]
                             Dufty, 1982 [C]
                             Rothstein et at., 1984 [C]
                             Teather and Robertson, 1985 [P]
Species                        Food         Resources Other
CLASS AVES                                            HB
Melanerpes formicivorus      QN
Centrocercus urophasianus                             HB
Ardea herodias               DS, PR
Pwphyrio p. melanotus        QN
Selasphorus rufus            QN
Calypte anna                                          EA
Family Anatidae                                PR
Family Scolopacidae          DS, PR, RE               PD
Tryngites subruficollis      DS, PR                   PD
Calidris alba                QN, DE
                             DS, QN, DE
Pluvialis squatarola                                  PO
Catoptrophorus semipalmatus  TY
Catharcta maccormicki        PR
Catharcta lonnbergi          PR
Stercorarius spp.            TY
Opisthocomus hoazin                                   HB
Corvus spp.                  QN
Garrulus glandarius          QN                       PO
Anthornis melanura           DS
Phainopepla nitens           QN, PR
Parus atricapillus           QN                       RF
                             DS, QL
Nectarinia reichenowi        QN
Vestiaria coccinea           QN
Phylidonyris nigra           QN
Phylidonyris novaehollandiae QN
Motacilla alba yarrelli      DS
Motacilla alba               QN
Motacilla alba alba          DS, QN, PR
Prunella modularis           DS, PR
Turdus migratorius           QN
Turdus merula                QN
Turdus philomelos            QN
Turdus pilaris               QN, PR, QL, AS
Myadestes townsendi          DS,QN
Tiaris olivacea                                       HB
Molothrus ater                                        HN
            Ecological variables listed by species of mammals.
                     Abbreviations as shown in Table 2
      Species                    Reference                      Food
Didelphis virginiana        Ryser, 1995 [C]                 DS, PR, QL
Oryctolagus cuniculus       Cowan and Bell, 1986 [C]
Order Primates              Mitani and Rodman, 1978 [C]     DS
Propithecus verreauxi       Richard, 1974 [C]               DS, QN
Papio ursinus               Hamilton et al. 1976 [C]
Presbytis melalophos        Bennett, 1986 [C]               DS, QN, PR
Cercopithecus aethiops lan- Kavanagh, 1981 [C]              QN, PR
Marmota monax               Ferron and Ouellet, 1989 [C]
Tamiasciurs spp.            Smith, 1968 [C]                 QN
Mus musculus                Davis, 1958 [E]
                            Anderson, 1961 [P, C]           DS, QN
                            Poole and Morgan, 1976 [E]
Mus musculus                Bronson, 1979 [P]               QN, PR
Clethrionomys rufocanus     Ims, 1987 [C]                   DS
                            Ims, 1988 [E]
Neotoma lepida latirostra   Vaughan and Schwartz, 1980 [C]  DS
Microtus agrestis           Nelson, 1995 [C, E]
Microtus californicus       Ostfeld, 1986 [P, E]            DS, QN, RE
Proechimys semispinosus     Adler et at., 1997 [C]          DS, RE, PR
Ursus americanus            Rogers, 1987 [P, C]             DS, QN, PR
                            Hellgren and Vaughan, 1990 [C]  DS, PR
Mustela nivalis             Lockie, 1966 [C]
Meles meles                 Kruuk and Parish, 1987 [C]      QN
Taxidea taxus               Goodrich and Buskirk, 1998 [C]  DS, QN, PR
Cerdocyon thous             Brady, 1979 cited in Moehlman,  TY
                              1989 [C]
Canis lupus                 Peterson, 1979 [C]              QN
Vulpes vulpes               Kolb, 1986 [P]
                            Tsukada, 1997 [C]               DS
Family Felidae              Liberg and Sandell, 1988 [P, C] DS, PR
Acinonyx jubatus            Caro and Collins, 1986 [C]      QN
Felis rufus                 Bailey, 1974 [P, C]             DS
                            Zezulak and Schwab, 1979 [C]
Felis domesticus            Liberg, 1980 [C]
                            Liberg, 1984 [C]
                            Konecny, 1987 [C]               QN, DS
Panthera tigris             Sundquist, 1981 [C]             DS, PR
Order Artiodactyla          Leuthold, 1977 [C]
Equus caballus              Rubenstein, 1981a [C]           DS, QL
Equus asinus                Woodward, 1979 [C]              DS, QN, PR
Hippopotamus amphibius      Karstad and Hudson, 1986 [C]
Cervus elaphus              Carranza et al., 1990 [C]       DS, QN
                            Carranza et al, 1995 [E]        DS, QN
                            Carranza et al., 1996 [C]       DS, QN
Odocoileus hemionus         Geist, 1981 [C]
Odocoileus h. columbianus   Miller, 1974 [C]                QN
Capreolus capreolus         Prior, 1968 [C]                 QN
Dama dama                   Langbein and Thirgood, 1989 [C]
      Species               Resources Other
Didelphis virginiana
Oryctolagus cuniculus                 RF
Order Primates              DS
Propithecus verreauxi
Papio ursinus               DS
Presbytis melalophos
Cercopithecus aethiops lan-           PD
Marmota monax                         PO
Tamiasciurs spp.
Mus musculus                          PO
                                      HB, SP
Mus musculus                          HB
Clethrionomys rufocanus               PO, MA
Neotoma lepida latirostra
Microtus agrestis                     MA, PO
Microtus californicus                 MA
Proechimys semispinosus               PO
Ursus americanus
Mustela nivalis                       PO
Meles meles
Taxidea taxus                         PO
Cerdocyon thous
Canis lupus
Vulpes vulpes                         HB
Family Felidae                        MA
Acinonyx jubatus
Felis rufus
Felis domesticus                      PO
                            DS        MA
Panthera tigris
Order Artiodactyla                    PO
Equus caballus
Equus asinus
Hippopotamus amphibius                SP
Cervus elaphus
Odocoileus hemionus         DS, QN
Odocoileus h. columbianus
Capreolus capreolus
Dama dama                             HB, PO
Gazella granti        Walther, 1977 [C]                                   HB
Oretragus oretragus   Jarman, 1974 [C]                                    HB
Kobus leche leche     Lent, 1969 [C]                                      HB
Aepyceros melampus    Warren, 1974 [C]                                    PO
                      Jarman, 1979 [C]                  QN, QL            PO
Antilocapra americana Bromley, 1977 [P]                 DS, QN, RE        HB
                      Kitchen and O'Gara, 1982 [C]                 DS, QL PO
                      Deblinger and Alldredge, 1989 [C] DS
                      Maher, 1994 [C]                   QN                PO
                      Byers, 1997 [C]                                     PO
      Summary of ecological variables reported for each taxon. Numbers
         represent number of papers citing that variable within that
        class. Numbers in parentheses are numbers of papers reporting
         on species in that class. Abbreviations as given in Table 2
                        Food                        Resources in general
Class                    DS    DE QN PR RE QL TY AS          DS          QU
Osteichthyes (N = 26)     6    0   4  4 0  0  2  0           0           0
Amphibia (N = 1)          1    0   0  0 0  0  0  0           0           0
Reptilia (N = 8)          2    0   4  0 0  0  0  0           1           0
Aves (N = 43)             9    2  22  7 1  2  3  1           0           0
Mammalia (N = 57)        22    0  22 12 2  4  1  0           6           1
Class                 QN PR PO PD HB SP MA RF IIN EA
Osteichthyes (N = 26) 0  0   8 0  7  4  0  4   0  0
Amphibia (N = 1)      0  0   0 0  1  0  0  0   0  0
Reptilia (N = 8)      0  0   2 1  0  0  1  0   0  0
Aves (N = 43)         0  1   3 2  4  0  0  1   3  1
Mammalia (N = 57)     1  0  16 1  8  3  8  1   0  0
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Publication:The American Midland Naturalist
Geographic Code:1USA
Date:Jan 1, 2000
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