|
|
Gillan DJ, Premack D, & Woodruff G. (1981). Reasoning in the chimpanzee: I. Analogical reasoning. J. Exp. Psychol.: Anim. Behav. Process., 7, 1.
|
|
|
|
Bruns, E. (1981). Estimation of the breeding value of stallions from the tournament performance of their offspring. Livestock Production Science, 8(5), 465–473.
Abstract: Data from horse-riding competitions recorded in Germany in 1976 and 1977 have been analysed to estimate genetic parameters for performance traits of riding horses measured in dressage, jumping competitions and trials. The performance traits analysed were logarithmic earnings per start, relative place number, and place value. The results are the following. 1. (1) Heritability and repeatability estimates for performance in dressage shows are 0.2 and 0.4 respectively. Corresponding estimates for performance in jumping competitions are 20% less. No genetic differences are found between stallions for performance in trials.2. (2) A selection index for estimating the breeding value of stallions was constructed by using the repeated performances of their offspring in dressage and jumping shows. For this purpose, performance data for at least ten progeny should be available. The correlation between the breeding values estimated from the dressage and jumping performances of the same stallions was approximately zero.3. (3) Reliable progeny-testing requires that the assumptions of mating stallions at random, selecting progeny randomly, and distributing them equally across environmental effects be fulfilled.4. (4) The genetic use of breeding values of stallions estimated from the performance of their progeny is opposed by the prolongation of the generation interval. This can be partly overcome by sampling young stallions and making use of the test results for young progeny only.
|
|
|
|
Kihara, H. (1981). Comparison of the redox reactions of various types of cytochrome c with iron hexacyanides. Biochimica et Biophysica Acta (BBA) – Bioenergetics, 634, 93–104.
Abstract: The dynamic behavior of various types of cytochromes c in the redox reaction with iron hexacyanides was studied using a temperature-jump method in order to elucidate the molecular mechanism of the redox reaction of cytochromes with their oxidoreductants. Transmittance after the temperature jump changed through a single exponential decay for all cytochromes investigated. Under a constant concentration of anion, the redox reaction of various types of cytochrome c with iron hexacyanides was analyzed according to the scheme: Ki=kt/k-i (i=1,2,3) where C(III) and C(II) are ferric and ferrous cytochromes, respectively, Fe(III) and Fe(II) are ferri- and ferrocyanides, respectively, C(III) [middle dot] Fe(II) is the ferricytochrome-ferrocyanide complex and C(II) [middle dot] Fe(III) is the ferrocytochrome-ferricyanide complex. When step B is slower than the other two steps A and C, τ-1 can be represented approximately as where the bar over the variables denotes the equilibrium value. In a large excess of ferrocyanide against cytochrome, we can estimate k2, k-2, K1 and K3 independently. In the case of horse cytochrome c at 18[degree sign]C in 0.1 M phosphate buffer at pH 7 with 0.3 M KNO3, the estimated parameters are k2 = 100 +/- 50 s-1, k-2 = (3.5 +/- 1.0) [middle dot] 103 s-1, K1 = 15 +/- 7 M-1 and K3 = (8.5 +/- 1.5) [middle dot] 10-4 M. From the same experiments for seven cytochromes (cytochrome c from horse, tuna, Candida krusei, Saccharomyces oviformis, Rhodospirillum rubrum cytochrome c2, Spirulina platensis cytochrome c-554 and Thermus thermophilus cytochrome c-552), the following results can be deduced. (1) Each parameter defined in the scheme above (k2, k-2, K1, K3) diverged beyond the error range. Above all, k2 values of cytochromes c-554 and c-552 are as large as 1 [middle dot] 104 s-1 and much larger than those for the other cytochromes (to 50 approx. 700 S-1). (2) The variance of k2K1 and k-2/K3 are relatively less than the variances of individual parameters (k2, k-2, K1 and K3), which suggests that the values of k2K1 and k-2/K3 have been conserved during the course of evolution.
|
|
|
|
Bean, P. (1981). Punishment: A Philosophical and Criminological Enquiry.
|
|
|
|
R. A. J. Taylor. (1981). The Behavioural Basis of Redistribution I. The Delta -Model Concept. T. J. Anim. Ecol., 50(2), 573–586.
Abstract: (1) A conceptual model is developed in which spatial behaviour is density-dependent. The behaviour is classified as congregatory or migratory according to whether it results in movement towards or away from population concentrations. (2) Spatial behaviour is shown to result from both individual and population interactions. (3) The stability properties of the model are explored and it is shown how, under particular conditions, populations obeying the model have a population density regulating mechanism. (4) The similarity between the model and the potential energy curve of physics is noted, but it is emphasized that this is a behavioural not a physical model.
|
|
|
|
Partridge, B. L. (1981). Internal dynamics and the interrelations of fish in schools. J Comp Physiol Sensory Neural Behav Physiol, 144(3), 313–325.
Abstract: The three-dimensional structure of schools of saithe (Pollachius virens) and the interactions between individuals over time were analyzed in 12,240 frames of videotape sampled at 2.7 Hz. Time series analyses of the interactions between identified individuals allowed testing of assumptions of anonymity vs. leadership in schools and investigation of the transfer of information between individuals by which collective decisions are made. Results include the following:1.Saithe match changes in both swimming direction and speed of their neighbors but correlations are greater for swimming speed. Average speed of the school does not greatly affect correlations between neighboring fish although the reaction latencies may be somewhat increased. As shown previously (Partridge et al. 1980) nearest neighbor distance (NND) decreases with increasing school velocity.2.Saithe simultaneously match the headings and swimming speeds of at least their first two nearest neighbors within the school (NN1 and NN2). Partialling out the correlation between a fish's neighbors demonstrates that a fish's correlation to his second nearest neighbor (NN2) is not simply a transitive function of mutual correlation between the NN1 and NN2.3.Several sources of individual variation in schooling performance were examined. In all respects except one, that of preferred positions within the school, saithe showed no individual differences, i.e., some were not “better schoolers” than others. Although fish in the school differed in length by up to a factor of 2.5, no size related effects in NND or nearest neighbor positioning were found.4.Single Linkage Cluster Analysis (SLCA) of the cross-correlations of fishs' swimming speeds and directions demonstrated quantitatively the existence of subgroups within schools if they contain more than 10-11 members. Subgroups acting more-or-less independently in terms of short term variations in speed and direction nonetheless remained within the school as a whole and were not often apparent to observers since members of one group interdigitated with those of another. How individuals know to which subgroup they belong remains unanswered.
|
|
|
|
Roberts, J., Hunter, M. L., & Kacelnik, A. (1981). The ground effect and acoustic communication. Anim. Behav., 29(2), 633–634.
|
|
|
|
Miller, R. (1981). Male aggression, dominance and breeding behaviour in Red Desert feral horses. Z. Tierpsychol., 57, 340–201.
|
|
|
|
Clutton-Brock, J. (1981). Domesticated animals from early times. Austin: Univ of Texas Press.
|
|
|
|
Barnard, C. J., & Sibly, R. M. (1981). Producers and scroungers: A general model and its application to captive flocks of house sparrows. Anim. Behav., 29(2), 543–550.
Abstract: Many forms of interaction within and between species appear to be based on `scrounger' individuals or species exploiting a limited resource provided `producers'. A mathematical model is presented which shows whether or not scroungers are maintained in a group, depending on their frequency and the group size. Some of the predictions of the model were tested in captive flocks of house sparrows Passer domesticus L. Here the scroungers obtained most of their food (mealworms) by interaction and the producers found most of their food by actively foraging: the pay-off to each type was measured as mealworm capture rate. Neither type changed strategy opportunistically in response to instantaneous flock composition but, not surprisingly, scroungers fared better when one of more producers were present. However, scrougers did much worse than expected when greatly outnumbered by producers, perhaps because producers then found the available food very quickly.
|
|
