The study of interspecific competition has long been one of ecology's most fashionable pursuits. Stimulated in part by a simple theory (Lotka 1932; Volterra 1926; Gause 1934; Hutchinson 1959; MacArthur and Levins 1967), ecologists gathered numerous data on the apparent ways species competitively coexist or exclude one another (reviews in Schoener 1974b, 1983). As is typical in science, most of the early data were observational, and the few experimental studies were mostly performed in the laboratory rather than in the field. Though never lacking its doubters, the belief in the natural importance of interspecific competition is now being severely questioned (review in Schoener 1982). Many of the putatively supportive observations have been challenged as being statistically indistinguishable from random contrivance. Most such attacks have been rebutted, but not without some modification of original conclusions (e.g., papers in Strong et al. 1983). New observations have been gathered for certain systems, suggesting a lack of competitively caused patterns and catalyzing the variable environment view of Wiens (1977) in which competition is seen as a temporally sporadic, often impotent, interaction. Other critics have charged that the lack of experimental field evidence for competition would preclude its acceptance regardless of the quality of observational data. Indeed, results of some of the earlier field experiments are in part responsible for competition's presently beleaguered state. Connell (1975), after reviewing the field experiments known to him through 1973, concluded that predation, rather than competition, appears to be the predominant ecological interaction and should be given "conceptual priority." Shortly afterward, Schroder and Rosenzweig (1975) showed experimentally that two species of desert rodents overlapping substantially in habitat did not appear to affect one another's abundances. This result was interpreted as contradicting a crucial assumption of competition theory, almost its linchpin: the greater the resource overlap between species, the greater the competition coefficient, a measure of the intensity of interspecific competition (relative to intraspecific competition; MacArthur and Levins 1967; review in Roughgarden 1979).

Field experiments on interspecific competition

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background--only basic calculus and statistics.

Ecological Models and Data in R

A number of experiments (Burnett 1956; Hassell & Huffaker 1969; Holling 1959; Ullyett 1949a,b, 1950) indicate that a basic assumption implicit in early population models of predator-prey and parasite-host interactions (Lotka 1925; Yolterra 1926; Nicholson & Bailey 1935) is false. This assumption requires the number of hosts parasitized (or prey attacked) to be proportional to the density of hosts and the density of parasites*. It is possible to formalize this assumption in terms of searching efflciency (E) where E is deSned by E Na (1)

/pdf/mutual-interference-between-parasites-or-predators-and-its-4z1di11ww2.pdf

Mutual interference between parasites or predators and its effect on searching efficiency

Insects that are parasitic only during their immature stages are termed protelean parasites (11). The protelean parasites that attack invertebrates nearly always de­ stroy their hosts. These parasites are often described as parasitoids, a term coined by Reuter (167) to differentiate them from the typical parasites. Parasitoids include a vast number of species of the so-called parasitic Hymenoptera, the Strepsiptera, and a few of the Diptera, primarily in the family Tachinidae. Although there are a few exceptions, insect parasitoids appear as typical parasites during their early developmental stages and later destroy the host to live as free adults. Placing emphasis on the latter aspects of their feeding behavior, Flanders (62) has recently referred to such insects as carniveroids. The evolutionary strategy of the parasitoid­ host relationship is different from that of either the predator or the parasite-host relationship in that the host's future development is of importance only to the parasitoid (226). The adult female parasitoid upon emergence is often in an alien habitat and removed from a host population. She must locate a suitable host in order to propa­ gate. Salt (179) concluded that the parasitoid first seeks a suitable environment. Laing (109) divided the host selection process into environmental and host factors and believed that the parasitoid is guided to a host habitat by chemical and physical parameters. Once a female has located a host habitat, she then searches systemat­ ically. Combining the information of Salt (179) and Flanders (60), Doutt (41) divided the process that results in successful parasitism into four steps: (a) host habitat location, (b) host location, (c) host acceptance, and (d) host suitability. More recently, a fifth step, host regulation, has been added (226) in order to adequately describe the factors necessary for successful parasitism. The first three of these steps can be combined as aspects of the host selection process. The host selection process may consist of only two or three steps in one relationship or of many steps in others. Because of this, there is often some overlap in describing and

Host selection by insect parasitoids

This paper summarizes models of estimation and analysis for the measure of consumer food preferences originally derived by Manly et al. (1972) and further developed by Chesson (1978). Unlike many alternative measure this measure of preference does not change with changes in food densities unless consumer behavior also changes. This measure is shown to relate in a simple way to parameters, such as clearance and attack rates, which appear in certain commonly used models of foraging behavior. See full-text article at JSTOR

https://www.jstor.org/stable/pdfplus/1937838.pdf

The Estimation and Analysis of Preference and Its Relatioship to Foraging Models

Population models for host-parasite interactions attempt to describe the outcome of parasite search by making simple assumptions about the way in which parasites find their hosts. Parasite behaviour is often described by precise mathematical equations, which may or may not have any biological validity. In most models, parasites are assumed to oviposit or search at random, and their success is calculated from equations of the type:

Random search and insect population models

A new method for the identification of key factors from life-table data.

SUMMARY (1) A method based on Moran curves is presented for determining monthly changes in density independent mortality acting on tsetse fly populations under natural conditions. (2) The method of analysis is tested on the output of a simple population model for tsetse and predicts qualitative changes in mortality under all conditions and quantitative changes when the mortality acts equally on all life stages. (3) Fly round records for female G. morsitans submorsitans from the Yankari Game Reserve, N. Nigeria, for the period 1964-73, are analysed using the new method. Mean monthly density independent mortalities are calculated and are shown to be most closely related to mean monthly saturation deficit. (4) Values of density independent mortality are superimposed on an annual climogram for Bauchi, near the study site, and mortality contours are drawn enclosing regions of equal mortality. This procedure identifies an environmental optimum for the subspecies, between 24 and 26? C and 5-13 mm Hg saturation deficit. (5) Less complete data from Zambia are also analysed and identify a similar optimum for G. m. morsitans, at between 22 and 23? C and 7-11 mm Hg saturation deficit. These two optima are compared with previous estimates derived by quite different methods. (6) Vertical sections taken through the mortality contours give rise to mortality profiles w~hich, in conjunction with the population model, can be used to define the bioclimatic limits of the species. (7) Weather records for ninety-one sites throughout tropical Africa, in both tsetse and non-tsetse areas, are summarized: 9400 of the sites within the present or recent known distribution of G. morsitans fall within the predicted bioclimatic limits, whilst only 5000 of non-tsetse areas (an average of less than 200 km away from the tsetse area nearest to each of them) do so. (8) The construction of bioclimatic limits also identifies an optimum saturation deficit at each temperature. It is suggested that the possibility of tsetse control in, or eradication from, any area is related to the distance of the mean environmental conditions from the predicted optimum at the same mean temperature. (9) Finally the problems of applying the analytical method to other data are briefly discussed.

David Rogers

Papers

Random search and insect population models

A new method for the identification of key factors from life-table data.

Tsetse population dynamics and distribution: a new analytical approach

The Dynamics of Arthropod Predator-Prey Systems

Study of a natural population of Glossina fuscipes fuscipes Newstead and a model of fly movement.