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We review the concepts and research associated with measuring fear and its consequences for foraging. When foraging, animals should and do demand hazardous duty pay. They assess a foraging cost of predation to compensate for the risk of predation or the risk of catastrophic injury. Similarly, in weighing foraging options, animals tradeoff food and safety. The foraging cost of predation can be modelled, and it can be quantitatively and qualitatively measured using risk titrations. Giving-up densities (GUDs) in depletable food patches and the distribution of foragers across safe and risky feeding opportunities are two frequent experimental tools for titrating food and safety. A growing body of literature shows that: (i) the cost of predation can be big and comprise the forager's largest foraging cost, (ii) seemingly small changes in habitat or microhabitat characteristics can lead to large changes in the cost of predation, and (iii) a forager's cost of predation rises with risk of mortality, the forager's energy state and a decrease in its marginal value of energy. In titrating for the cost of predation, researchers have investigated spatial and temporal variation in risk, scale-dependent variation in risk, and the role of predation risk in a forager's ecology. A risk titration from a feeding animal often provides a more accurate behavioural indicator of predation risk than direct observations of predator-inflicted mortality. Titrating for fear responses in foragers has some well-established applications and holds promise for novel methodologies, concepts and applications. Future directions for expanding conceptual and empirical tools include: what are the consequences of foraging costs arising from interference behaviours and other sources of catastrophic loss? Are there alternative routes by which organisms can respond to tradeoffs of food and safety? What does an animal's landscape of fear look like as a spatially explicit map, and how do various environmental factors affect it? Behavioural titrations will help to illuminate these issues and more.

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Abiraterone treats metastatic castrate-resistant prostate cancer by inhibiting CYP17A, an enzyme for testosterone auto-production. With standard dosing, evolution of resistance with treatment failure (radiographic progression) occurs at a median of ~16.5 months. We hypothesize time to progression (TTP) could be increased by integrating evolutionary dynamics into therapy. We developed an evolutionary game theory model using Lotka–Volterra equations with three competing cancer “species”: androgen dependent, androgen producing, and androgen independent. Simulations with standard abiraterone dosing demonstrate strong selection for androgen-independent cells and rapid treatment failure. Adaptive therapy, using patient-specific tumor dynamics to inform on/off treatment cycles, suppresses proliferation of androgen-independent cells and lowers cumulative drug dose. In a pilot clinical trial, 10 of 11 patients maintained stable oscillations of tumor burdens; median TTP is at least 27 months with reduced cumulative drug use of 47% of standard dosing. The outcomes show significant improvement over published studies and a contemporaneous population.