The main proponent of management of any animal species is habitat management. The ability of habitats to maintain species communities will depend on the variation in both habitat structure and composition. While spatial variation in habitat resources plays a critical role in determining the distribution of species, an equally important consideration that must be accounted for is temporal variation in the needs of the target species. Nutritional requirements, and thus the habitats used to fulfil those nutritional needs, will be different depending on if the individual is breeding, migrating, molting, enduring winter, or establishing a new range. For waterfowl, we currently assume that winter and migration are nutritionally stressful and are consequently the periods most limiting to populations. The theory of ideal free distribution assumes that animals distribute themselves according to the factor most limiting to their fitness. In the case of non-breeding waterfowl, this factor is believed to be food. We assume if habitats with abundant food resources are provided, waterfowl will make use of those habitats. Deviations from an ideal free distribution based on food become problematic for managers since these deviations will keep some areas from being exploited to their potential, while other areas may become over-exploited. Recent observations have made it clear that this assumption may need to be reconsidered for effective waterfowl management. In this dissertation I quantitatively examine the degree to which spring migrating waterfowl conform to, or deviate from, an ideal free distribution based on food. Since food availability was not expected to account for 100% of waterfowl distribution, I further investigated what other potential habitat components influence the distribution of spring migrating waterfowl. In the first chapter of this dissertation, I explicitly tested the influence of food availability on waterfowl distribution. A series of paired 0.42 ha (1 acre) plots were established in various habitat types. One plot in each pair was treated with corn to a density of 2000 kg/ha, while the remaining plot was used as a control. Background food availability was controlled for by taking core samples from each plot, and estimating the natural seed and invertebrate biomass. The abundance each species of waterfowl using the plots was recorded during morning and afternoon observation periods. Linear mixed models were used to assess how variations in food availability influenced distribution of waterfowl. Although the waterfowl community showed a significant preference for treatment plots, our ability to influence abundance was low. Food availability accounted for minimal variation in abundance of the waterfowl community as a whole or for each focal species. Since the results of the first chapter showed food availability to be a poor predictor of waterfowl distribution, in the second chapter I set out to determine other potential habitat variables could be responsible for driving waterfowl distribution during spring migration. After each observation period, a series of habitat structural measurements were made within each paired plot. Habitat measurements included water characteristics, vegetation structure, vegetation type, habitat type, and weather conditions. Linear mixed models and model selection were employed to determine which of the habitat characteristics showed the greatest ability to predict waterfowl abundance on study plots. Models containing precipitation and Wabash River flood stage predictor variables were the best performing, and were the best predictors of waterfowl abundance on study plots. The results from this chapter encouraged investigation into how environmental factors shape the formation of local duck communities are structured from regional pools. In the third chapter of this dissertation I investigate the relationship between local and regional waterfowl community structure and how this relationship is mediated through environmental filters which dictate what proportion of the regional species pool exists at local scales. To address this relationship, I tested three hypotheses: 1) resource availability drives species diversity at local scales; 2) similarity between local and regional habitats will result in a similar species community occurring at both scales, and; 3) increased heterogeneity of local habitat structure will result in more diverse waterfowl communities at local scales. I used Mahalanobis distance and cumulative standard deviation of habitat variables in conjunction with mixed models and model selection to compare hypotheses and determine which had the greatest potential for mediating local community structure from regional pools. Increasing resource abundance appeared to have the greatest influence over local duck diversity, but the model indicated that although species diversity could be increased by increasing food abundance, diversity at local scales would become saturated before becoming representative of the regional community.

Charnov's (1976) marginal value theorem has had success in predicting that animals will optimize net rate of gain when foraging in a patchy environment. The present study attempts to apply the marginal value theorem (MVT) to human behavior in a business setting in 3 Experiments. Businesses also attempt to optimize net rate of gain when choosing to discontinue one product in lieu of another using a product life cycle (PLC). Experiments 1 & 2 attempted to assess human behavior in a business context by varying time necessary to retool and monetary cost of retooling respectively. Experiment 3 attempted to add ecological validity by introducing variability to the PLC. The results of Experiments 1, 2, & 3 indicate that the MVT does not accurately predict human behavior in a business context, though methodological issues may have affected these results. Future research must be conducted in this area.

In urban search and rescue (USAR) operations, there is a considerable amount of danger faced by rescuers. The use of mobile robots can alleviate this issue. Coordinating the search effort is made more difficult by the communication issues typically faced in these environments, such that communication is often restricted. With small numbers of robots, it is necessary to break communication links in order to explore the entire environment. The robots can be viewed as a broken ad hoc network, relying on opportunistic contact in order to share data. In order to minimise overheads when exchanging data, a novel algorithm for data exchange has been created which maintains the propagation speed of flooding while reducing overheads. Since the rescue workers outside of the structure need to know the location of any victims, the task of finding their locations is two parted: 1) to locate the victims (Search Time), and 2) to get this data outside the structure (Delay Time). Communication with the outside is assumed to be performed by a static robot designated as the Command Station. Since it is unlikely that there will be sufficient robots to provide full communications coverage of the area, robots that discover victims are faced with the difficult decision of whether they should continue searching or return with the victim data. We investigate a variety of search techniques and see how the application of biological foraging models can help to streamline the search process, while we have also implemented an opportunistic network to ensure that data are shared whenever robots come within line of sight of each other or the Command Station. We examine this trade-off between performing a search and communicating the results.

Optimal Foraging Theory (OFT) has its origin in processualistic ideas in 1960s with traces back to the dawn of the archaeological science in the 19th century. The OFT model is based on the construction of an individual’s food item selection understood as an evolutionary construct that maximizes the net energy gained per unit feeding time. The most common variants are diet patch choice, diet breadth/prey choice models and Marginal Value Theorem (MVT). The theory introduced experimental studies combined with mathematically data analyses and computer simulations. The results visualized in the experimental diagrammed curve are possible to compare with the archaeological records. What is “optimal” is an empirical question not possible to know but still useful as a benchmark for measuring culture. The theory is common in USA but still not in Europe. OFT seems to be useful in hunter-gatherer research looking at human decisions, energy flow, depression of resources and extinction. This literature review concludes that the prey-choice/diet-breadth model seems to be useful for hunter-gatherer research on Gotland focusing on possible causes of the hiatus in archaeological records between 5000-4500 BC. / Optimal Foraging Theory (OFT) har sitt ursprung i de processualistiska ideérna under 1960-talet med spår tillbaka till arkeologins början som vetenskap under 1800-talet. OFT modellen baseras på konstruktionen av en individs födoämnesval som förstås som en evolutionär konstruktion som maximerar nettoenergiintaget per tidsenhet som gått åt för försörjningen. De vanligaste varianterna är patch-choice, diet breadth/prey choice modellerna och Marginal Value Theorem (MVT). Experimentella studier genomförs och data bearbetas matematiskt och visar datorsimulerade kurvdiagram möjliga att jämföra med arkeologiska källmaterial. Vad som är ”optimalt” är en empirisk fråga omöjlig att veta men användbar ändå som en slag referens för att mäta kultur. Teorin är vanlig i USA men ännu inte i Europa. OFT förefaller användbar inom forskning av jägare-samlare om man fokuserar på beslutsfattande, energiflöde, depression av resurser och utrotning av arter. Slutsatsen i denna litteraturöversikt är att prey choice/diet breadth modellen tycks vara användbar för gotländsk jägare-samlare-forskning som fokuserar på möjliga orsaker till de arkeologiska fyndens hiatus mellan 5000-4500 BC.

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It is generally accepted that the Marginal Value Theorem (MVT) describes optimal foraging strategies. Some research findings, however, indicate that in natural conditions foragers not always behave according to the MVT. To address this inconsistency, in a series of computer simulations, I examined the behaviour of four types of foragers having specific foraging efficiencies and using the MVT and alternative strategies in 16 simulated landscapes in an ideal environment (no intra- and inter-species interactions). I used data on elk (Cervus elaphus) to construct the virtual forager. Contrary to the widely accepted understanding of the MVT, I found that in environments with the same average patch quality and varying average travel times between patches, patch residence times of some foragers were not affected by travel times. I propose a mechanism responsible for this observation and formulate the perfect forager theorem (PFT). I also introduce the concepts of a foraging coefficient (F) and foragers hub (), and formulate a model to describe the relationship between the perfect forager and other forager types. I identify situations where a forager aiming to choose an optimal foraging strategy and maximize its cumulative consumption should not follow the MVT. I describe these situations in a form of a mathematical model. I also demonstrate that the lack of biological realism and environmental noise are not required to explain the deviations from the MVT observed in field research, and explain the importance of scale in optimal foraging behaviour. I also demonstrate that smart foraging, which is a set of rules based on key ecological concepts: the functional response curve (FRC), satisficing, the MVT, and incorporates time limitations, should allow for fitness maximization. Thus, it should be an optimal behavior in the context of natural selection. I also demonstrate the importance of the FRC as a driver for foraging behaviors and argue that animals should focus more on increasing the slope of their FRC than on choosing a specific foraging strategy. Natural selection should, therefore, favor foragers with steep FRC. My findings introduce new concepts in behavioural ecology, have implications for animal ecology and inform wildlife management.

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