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In a 4—yr study of the reproductive strategies of Cooper's Hawks (Accipiter cooperii) nesting in north—central New Mexico, >50% of the females deserted during the fledgling—dependency period and did not renest. A dynamic state variable model was developed to study the females' brood—rearing strategies. In this model a strategy consisted of combinations of staying at the nest, hunting, and deserting. The modeling assumptions were: a female's strategy during brood rearing maximizes her reproductive fitness, defined as the weighted average of the expected probability of survival of ether current offspring and her expected future reproduction; and the reproductive fitness function depends on the physical condition of the female and nestlings, the risk to the nestlings associated with each strategy, and the male's foraging capabilities. The model predictions were compared to the observations of female strategies in this population of Cooper's Hawks. To insure a valid comparison, the model parameters were estimated from sources other than the observed population. The best match between observations and predictions (84—96%) was obtained when the nestlings' survival and the female's future reproductive potential were equally weighted during the nestlings stage, but weighted in favor of the female's productive potential during the fledgling stage. A sensitivity analysis showed that the model predictions corresponded well with the observations of staying and hunting at all parameters bounds. However, those combinations of parameter values that reflected conditions with the least pressure to desert missed 70—85% of the desertions. The sensitivity analysis also indicated that a key factor influencing the female's choice of strategy was the interaction between the threat to her future reproduction due to her poor physical condition and the nestlings's risk of death from predation and exposure. The agreement of model predictions and observed strategies supported the modeling assumptions. These results combined with the sensitivity analysis indicated that dynamic state variable modeling is an excellent tool for studying mate desertion.

This article reviews some of the current guidance concerning the separation of variability and uncertainty in presenting the results of human health and ecological risk assessments. Such guidance and some of the published examples of its implementation using two-stage Monte Carlo simulation methods have not emphasized the fact that there is considerable judgment involved in determining which input parameters can be modeled as purely variable or purely uncertain, and which require explicit treatment in both dimensions. Failure to discuss these choices leads to confusion and misunderstanding of the proposed methods. We conclude with an example illustrating some of the reasoning and statistical calculations that might be used to inform such choices.

Designing biomaterials to mimic and function within the complex mechanobiological conditions of connective tissues requires a detailed understanding of the micromechanical environment of the cell. The objective of our study was to measure the in situ cell-matrix strains from applied tension in both tendon fascicles and cell-seeded type I collagen scaffolds using laser scanning confocal microscopy techniques. Tendon fascicles and collagen gels were fluorescently labelled to simultaneously visualise the extracellular matrix and cell nuclei under applied tensile strains of 5%. There were significant differences observed in the micromechanics at the cell-matrix scale suggesting that the type I collagen scaffold did not replicate the pattern of native tendon strains. In particular, although the overall in situ tensile strains in the matrix were quite similar (∼2.5%) between the tendon fascicles and the collagen scaffolds, there were significant differences at the cell-matrix boundary with visible shear across cell nuclei of >1 μm measured in native tendon which was not observed at all in the collagen scaffolds. Similarly, there was significant non-uniformity of intercellular strains with relative sliding observed between cell rows in tendon which again was not observed in the collagen scaffolds where the strain environment was much more uniform. If the native micromechanical environment is not replicated in biomaterial scaffolds, then the cells may receive incorrect or mixed mechanical signals which could affect their biosynthetic response to mechanical load in tissue engineering applications. This study highlights the importance of considering the microscale mechanics in the design of biomaterial scaffolds and the need to incorporate such features in computational models of connective tissues.

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