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Cooperative behaviours result in the evolution of cheats: individuals that benefit from the behaviour without sharing the costs required to generate the behaviour. Normally the proportion of cheats is small, as large numbers of cheats will result in the breakdown of the behaviour. Using empirical and simulation-derived results we demonstrate a cooperative behaviour (aggregation between two species of intertidal snails that provides a benefit by reducing desiccation stress) that shows many characteristics similar to those of a cooperative system with cheats present. In this system, the high rocky shore littorinid Echinolittorina malaccana forages for longer after high water than Echinolittorina radiata, which stops foraging and begins to form aggregations earlier. Nevertheless, E. malaccana, the 'cheat' in this system, still occupies an equal proportion of the most beneficial places in aggregations. Computer simulations demonstrate that up to 65% of individual snails can show the behaviour of E. malaccana before the breakdown of this aggregation behaviour begins to occur through aggregations becoming smaller, and hence less effective against desiccation. The high proportion of 'cheats' possible in this cooperative behaviour implies that different selective pressures may act on individuals of different species in multi-species cooperative behaviours to those acting on individuals engaging in single species cooperative behaviours. Social symbiosis appears to be occurring between the species, but it appears that both mutualistic and parasitic symbioses are occurring. [ABSTRACT FROM AUTHOR]

Identifying individual animals is important in understanding their ecology and behaviour, as well as providing estimates of population sizes for conservation efforts. We produce identification keys from photographs of green sea turtles to identify them while foraging in Akumal Bay,Mexico. We create three keys, which (a) minimise the length of the key, (b) present the most obvious differential characteristics first, and (c) remove the strict dichotomy from key b. Keys were capable of identifying >99% of turtles in >2500 photographs during the six-month study period. The keys differed significantly in success rate for students to identify individual turtles, with key (c) being the best with >70% success and correctly being followed further than other keys before making a mistake. User-friendly keys are, therefore, a suitable method for the photographic identification of turtles and could be used for other large marine vertebrates in conservation or behavioural studies. [ABSTRACT FROM AUTHOR]

Many intertidal snails form aggregations during emersion to minimize desiccation stress. Here we investigate possible mechanisms for the evolution of such behavior. Two behavioral traits (following of mucus trails, and crevice occupation), which both provide selective advantages to individuals that possess the traits over individuals that do not, result in self-organization of aggregations in crevices in the rock surface. We suggest that the existence of self-organizing aggregations provides a mechanism by which aggregation behavior can evolve. The inclusion of an explicitly coded third behavior, aggregation, in a simulated population produces patterns statistically similar to those found on real rocky shores. Allowing these three behaviors to evolve using an evolutionary algorithm, however, results in aggregation behavior being selected against on shores with high crevice density. The inclusion of broadcast spawning dispersal mechanisms in the simulation, however, results in aggregation behavior evolving as predicted on shores with both high crevice density and low crevice density (evolving in crevices first, and then both in crevices and on flat rock), indicating the importance of environmental interactions in understanding evolutionary processes. We propose that self-organization can be an important factor in the evolution of group behaviors. [ABSTRACT FROM AUTHOR]

Estimation of small mammal population sizes is important for monitoring ecosystem condition and for conservation. Here, we test the accuracy of standard methods of population size estimation using Capture-Mark-Recapture (CMR) on a simulated population of agents. The use of a computer simulation allows complete control of population sizes and behaviors, thereby avoiding assumptions that may be violated in real populations. We find that the recommended protocol for CMR sampling, using uniformly distributed traps, consistently overestimates population sizes by as much as 100% when studies are conducted over only two trapping periods. More than 20 trapping periods are required before this method, or that of placing traps randomly, gives an accurate estimation of population size (i.e., within a 95% confidence limit of the actual value). Non-random sampling, by placing traps on runways used by small mammals, produces the most accurate, and least variable, estimates of population. However, we show that around 10 trapping periods are still required to produce an accurate population estimate using this method. Given that most real populations do not comply with the ‘ideal’ assumptions made by CMR, we suggest that population estimates based on CMR may be fundamentally flawed, and recommend that protocols for CMR population estimation methods may need revising. [Copyright &y& Elsevier]