This study was a comprehensive evaluation of population reconstruction techniques. Population reconstruction techniques are population estimation methods that calculate a minimum population size based on age-specific harvest data (Downing 1980, Roseberry and Woolf 1991). Population reconstruction techniques share the following characteristics: 1) utilization of catch-at-age data and 2) backward addition of cohorts to estimate a minimum population size. I developed a questionnaire to survey the biologists participating in this survey to determine the most common reconstruction technique used to estimate population sizes of exploited white-tailed deer (Odocoileus virginianus) and black bear (Ursus americanus). Downing reconstruction (Downing 1980) was the most commonly used reconstruction technique among biologists participating in this study. Based on a comprehensive literature review and discussions with state biologists, I decided to evaluate virtual reconstruction (Roseberry and Woolf 1991) and develop a new reconstruction technique: Reverse Order reconstruction. I developed a quantitative population model in Microsoft Visual Basic 6.0 to evaluate the ability of the 3 reconstruction techniques to estimate population sizes given a variety of conditions. I evaluated the effects of stochasticity on reconstruction population estimates by incorporating different levels of environmental stochasticity (i.e. process error) and measurement error in the generated or "known" population. I also evaluated the effects of collapsing age classes and aging biases on population estimates. In all conditions, Downing and virtual reconstruction were underestimates of the actual population size. Reverse Order reconstruction more closely estimated the actual population size, but is also more data-intensive than the other 2 methods. Measurement error introduces more uncertainty in the reconstructed population estimates than does process error. The population simulation model proved that Downing and virtual reconstruction are consistently underestimates and the percent underestimation is due to lack of inclusion of a natural mortality rates in population estimation. I used the results of the questionnaire to characterize the harvest datasets of the states participating in this study. From these results, I chose two harvest datasets to further analyze: a white-tailed deer harvest dataset from North Carolina and a black bear harvest dataset from Pennsylvania. I analyzed these datasets with Downing and virtual reconstruction. I also applied the quantitative population model to these datasets to evaluate the effect of increasing levels of measurement error on the variance of the population estimates. I found that Downing and virtual reconstruction estimated the population sizes very closely to one another, within 5%, for both datasets, and the reconstructed estimates closely tracked the actual harvest numbers. I also found that increasing levels of measurement error increased the variance associated with reconstructed population estimates and may decrease the ability of these techniques to accurately capture population trends. / Master of Science

The importance of abiotic influences on the strength of biotic interactions is largely unknown. To explain large annual fluctuations in the population size of the tropical lizard, Anolis limifrons, on Barro Colorado Island, Panama, I hypothesized that annual variation in lizard population size is the result of modifications in the rate of predation on lizard eggs by Solenopsis ants induced by annual variation in wet season rainfall. I tested this hypothesis by manipulating water availability on experimental plots to Simulate the wettest (HW) and driest (LW) wet seasons in the last twenty years. The mean time to find and attack eggs by Solenopsis ants was significantly shorter on HW plots (range=6.6-21.7 days) than LW plots (range=17.8-30.8 days). Exponential models that regressed time on the cumulative percent mortality indicated that 1) the rate of predation was 3-5 times faster on HW plots than LW plots and 2) the predicted mortality of lizard eggs during their 42 day incubation period was 82.2-95.7% on HW plots and 56.1-58.6% on LW plots. Thus, the amount of rainfall during the wet season affected the population size of A. limifrons by modifying the strength of the interaction between Solenopsis ants and the eggs of A. limifrons. / Master of Science

Natural ecologies are prone to stochastic effects and changing environments that shape their dynamical behavior. Ecological systems can be modeled through relatively simple population dynamics models. There is a plethora of models describing deterministic models of ecological systems evolving in a constant environment. However, stochasticity can lead to extinction or fixation events, noise-stabilized patterns, and nontrivial correlations. Likewise, changing environments can greatly affect the behavior and ultimate fate of ecological systems. In fact, the dynamics of evolution are mostly driven by randomness and changing environments. Therefore, it is of utmost importance to develop population dynamics models that are able to capture the effects of noise and environmental drive. In this thesis, we use both theoretical tools and simulations to investigate population dynamics in the following contexts: We study the stochastic spatial Lotka-Volterra (LV) model for predator-prey interaction subject to a periodically varying carrying capacity. The LV model with on-site lattice occupation restrictions that represent finite food resources for the prey exhibits a continuous active-to-absorbing phase transition. The active phase is sustained by spatio-temporal patterns in the form of pursuit and evasion waves. Monte Carlo simulations on a two-dimensional lattice are utilized to investigate the effect of seasonal variations of the environment on species coexistence. The results of our simulations are also compared to a mean-field analysis. We find that the parameter region of predator and prey coexistence is enlarged relative to the stationary situation when the carrying capacity varies periodically. The stationary regime of our periodically varying LV system shows qualitative agreement between the stochastic model and the mean-field approximation. However, under periodic carrying capacity switching environments, the mean-field rate equations predict period-doubling scenarios that are washed out by internal reaction noise in the stochastic lattice model. Utilizing visual representations of the lattice simulations and dynamical correlation functions, we study how the pursuit and evasion waves are affected by ensuing resonance effects. Correlation function measurements indicate a time delay in the response of the system to sudden changes in the environment. Resonance features are observed in our simulations that cause prolonged persistent spatial correlations. Different effective static environments are explored in the extreme limits of fast- and slow periodic switching. The analysis of the mean-field equations in the fast-switching regime enables a semi-quantitative description of the stationary state. The mean-field analysis of the Lotka-Volterra predator-prey model with seasonally varying carrying capacity is extended to the resonant regime. This is done by introducing a homotopy mapping from this model to another model that allows for the application of Floquet theory. The stability of the coexistence fixed point is studied and the period doubling is related to a bifurcation point in the homotopy mapping. However, we find that the predator-prey ecology's coexistence is stable for most of its parameter region. We apply a perturbative Doi–Peliti field-theoretical analysis to the stochastic spatially extended symmetric Rock-Paper-Scissors (RPS) and May–Leonard (ML) models, in which three species compete cyclically. Compared to the two-species Lotka–Volterra predator-prey (LV) model, according to numerical simulations, these cyclical models appear to be less affected by intrinsic stochastic fluctuations. Indeed, we demonstrate that the qualitative features of the ML model are insensitive to intrinsic reaction noise. In contrast, and although not yet observed in numerical simulations, we find that the RPS model acquires significant fluctuation-induced renormalizations in the perturbative regime, similar to the LV model. We also study the formation of spatio-temporal structures in the framework of stability analysis and provide a clearcut explanation for the absence of spatial patterns in the RPS system, whereas the spontaneous emergence of spatio-temporal structures features prominently in the LV and the ML models. Stochastic reaction-diffusion models are employed to represent many complex physical, biological, societal, and ecological systems. The macroscopic reaction rates describing the large-scale, long-time kinetics in such systems are effective, scale-dependent renormalized parameters that need to be either measured experimentally or computed by means of a microscopic model. In a Monte Carlo simulation of stochastic reactiondiffusion systems, microscopic probabilities for specific events to happen serve as the input control parameters. To match the results of any computer simulation to observations or experiments carried out on the macroscale, a mapping is required between the microscopic probabilities that define the Monte Carlo algorithm and the macroscopic reaction rates that are experimentally measured. Finding the functional dependence of emergent macroscopic rates on the microscopic probabilities (subject to specific rules of interaction) is a very difficult problem, and there is currently no systematic, accurate analytical way to achieve this goal. Therefore, we introduce a straightforward numerical method of using lattice Monte Carlo simulations to evaluate the macroscopic reaction rates by directly obtaining the count statistics of how many events occur per simulation time step. Our technique is first tested on well-understood fundamental examples, namely restricted birth processes, diffusion-limited two-particle coagulation, and two-species pair annihilation kinetics. Next we utilize the thus gained experience to investigate how the microscopic algorithmic probabilities become coarse-grained into effective macroscopic rates in more complex model systems such as the Lotka–Volterra model for predator-prey competition and coexistence, as well as the rock-paper-scissors or cyclic Lotka–Volterra model as well as its May–Leonard variant that capture population dynamics with cyclic dominance motifs. Thereby we achieve a more thorough and deeper understanding of coarse-graining in spatially extended stochastic reactiondiffusion systems and the nontrivial relationships between the associated microscopic and macroscopic model parameters, with a focus on ecological systems. The proposed technique should generally provide a useful means to better fit Monte Carlo simulation results to experimental or observational data. / Doctor of Philosophy / Population dynamics models describe how the number of individuals of interacting species changes over time. This is used to understand the ultimate fate of ecological systems. An ecological system can exhibit long-time multi-species coexistence, the fixation of just one species (all other species go extinct), or total extinction of the system. Understanding the dynamics of the system can help predict the final state of the system from early observations, also, it can inform possible ways to steer the system into a desirable outcome. However, it is very difficult to model such systems due to their complexity. While great progress has been made in understanding well-mixed populations in constant environments, there is still much to learn about ecological systems under spatial and environmental variability. A complete understanding of ecological dynamics and how they couple to evolutionary dynamics requires models of populations that are random, and that take into account how different species might be more or less dominant in different environments. We contribute to investigating these models in the following way: Seasonal variations in temperature leads to a change in the availability of different crops. This affects the resources available for animal species to consume in one season compared to another season (e.g. summer and winter). We study a predator-prey model wherein the resource abundance available to the prey vary between two seasons. We showcase how this affects the system's coexistence regime, and spatial patterns. Cyclic models of predation are models where the food chain is cyclic, meaning that there is no "food chain" but rather a "food circle". We utilize theoretical tools to gain a better understanding of the spontaneous formation of well-known spatial patterns in cyclic predation models. The aim of population dynamics is to write a simple set of equations or models that can accurately capture the behavior of natural ecologies. This is rarely an easy task, because even if the microscopic interactions between species is known, it is very difficult to simplify this microscopic model to a simple set of macroscopic equations. We develop a technique that uses computer simulations to map microscopic interactions into simple rate equations. This work can inform better modeling of observational data.

Many management strategies are available to fishery managers to improve the sustainability of a fishery; however, it is not always clear how implemented strategies interact with the demographics of the exploited species. Management decisions are often made in order to maximize egg production and recruitment or to preserve specific size classes to increase reproductive output. Consequences of these strategies could include variation from a natural size structure of the population, exaggerated sexual dimorphism, skewed sex ratios, and suboptimal mating conditions. To examine the possibility of these consequences, I ran a series of deterministic models to simulate the fished and unfished population dynamics of two clawed lobster species, American lobster (Homarus americanus) and European lobster (Homarus gammarus), under a variety of management strategies. Protection of ovigerous females takes two forms in this model. The American fishery in the Gulf of Maine requires fishers to v-notch ovigerous females for up to four years of protection from fishing. The European fishery in southern Norway bans the harvest of ovigerous females, which translates to one year of protection. I compared the relative impact of the two levels of ovigerous female protections on factors that may be important for reproductive success: size structure, dimorphism, sex ratio, and egg production for both species. I then considered a case study on European lobster to evaluate the interaction of a no-take marine protected area with a slot limit to compare relative impacts to egg production, overall size structure and dimorphism. Results showed that American lobster females benefitted greatly from strict protections such as v-notching in terms of mean size increase and egg production, but mean size dimorphism and the overall proportion of females also increased with higher fishing pressure. European lobster females also benefitted from protections, but less dramatically than American lobsters, and with lower size dimorphism. In the case study, European lobsters benefited most from the implementation of a no-take marine protected area in combination with a slot limit to preserve the largest individuals of both sexes which improved overall egg production. By taking a simulation approach to evaluate these different management strategies on two closely related species of lobster, this thesis provides a basis for understanding how fishery decisions can achieve their sustainability goals in addition to quantifying some of the unintended impacts of management on parameters that may be important to overall reproductive success. / Master of Science / Fishery managers make decisions about a fishery based on the species' biology to optimize catch while also ensuring that enough individuals remain to keep the population alive for years to come. However, it is not always clear what types of unintended consequences these decisions may have. Management decisions are often made in order to maximize egg production, to keep small individuals alive until they can reproduce, or to preserve the large individuals that have high reproductive potential. Some consequences of these strategies could include a reduction in the number of large individuals with high fishing pressure, increased female body size compared to males, unequal numbers of females and males, and less optimal conditions for mating. To examine the possibility of these consequences, I ran a series of models to simulate the fished and unfished populations of two clawed lobster species, American lobster (Homarus americanus) and European lobster (Homarus gammarus), under a variety of management strategies. The American lobster fishery in the Gulf of Maine requires a practice known as v-notching, which protects egg-bearing females for up to four years. The Norwegian fishery for European lobster bans the harvest of egg-bearing females, which is protection that lasts for one year. I compared the impact of the two types of egg-bearing female protections on factors that may be important for reproductive success: abundance of large lobsters, unequal numbers of females and males, difference in size between females and males, and overall production of eggs for both species. I then considered a case study on European lobster to test how a no-take marine protected area and a slot limit (minimum and maximum harvest size limits) affected those same factors. Results showed that American lobster females benefited greatly from longer lasting protections by growing to larger sizes and producing more eggs, but the average size difference between females and males and the overall proportion of females also increased as fishing became more intense. European lobster females also benefitted from protections, but less dramatically than American lobsters, and with lower mean differences in size between females and males. In the case study, European lobsters benefitted most from the no-take marine protected area in combination with a slot limit to preserve the largest individuals of both sexes which improved overall egg production. Using a simulation makes it easier to tease apart the effects of these different management strategies on two closely related species of lobster. This thesis helps managers see how fishery decisions affect lobsters in both desired and unintended ways. With this information, managers can better improve the sustainability of the fishery through considering what a specific species needs to improve reproductive success.

范家偉. / 論文(博士)--香港中文大學歷史學部, 1997. / 附參考文獻. / 中英文摘要. / Available also through the Internet via Dissertations & theses @ Chinese University of Hong Kong. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Fan Jiawei. / Lun wen (Bo shi)--Xianggang Zhong wen da xue li shi xue bu, 1997. / Fu can kao wen xian. / Zhong Ying wen zhai yao.

Mountaintop removal mining (MTR) is a notorious stressor of stream ecosystems in the Central Appalachians. Valley fills (VF) lead to reduced occupancy, abundance, and species richness of stream salamanders. Multiple factors may be responsible for these reductions, but specifically habitat fragmentation and degradation may reduce colonization rates and increase local extinction rates. From 2013-2015, repeated counts of salamanders were conducted in stream reaches impacted by MTR/VF and compared to counts in reference reaches to answer the question: do stream salamander population dynamics differ between stream reaches impacted by MTR/VF and reference stream reaches? I also investigated dynamics of stream habitat using measures relevant to stream salamander persistence. Accordingly, I examined number of cover objects, percent detritus, hydroperiod, and specific conductance. From the salamander capture data, colonization and survival probabilities were lower in MTR/VF reaches than reference reaches. MTR/VF reaches also had fewer cover objects, higher percent detritus, constant stream flow, and elevated specific conductance. Although specific conductance was increased in MTR/VF reaches, it was not strongly correlated with colonization and survival. I suggest reduced rates of colonization and survival in MTR/VF stream reaches are driven by inhibited dispersal and reduced individual survival due to degraded terrestrial and aquatic environments.

Natural populations may be managed by humans for a number of reasons, with mathematical modelling playing an increasing role in the planning of such management and control strategies. In an increasingly heterogeneous, or `patchy' landscape, the interactions between distinct groups of individuals must be taken into account to predict meaningful management strategies. Invasive control strategies, involving reduction of populations, such as harvesting or culling have been shown to cause a level of disturbance, or spatial perturbation, to these groups, a factor which is largely ignored in the modelling literature. In this thesis, we present a series of deterministic, differential equation models which are used to investigate the impact of this disturbance in response to control. We address this impact in two scenarios. Firstly, in terms of a harvested population, where extinction must be prevented whilst maximising the yield obtained. Secondly, we address the impact of disturbance in an epidemic model, where the aim of the control strategy is to eradicate an endemic pathogen, or to prevent the invasion of a pathogen into a susceptible population. The movement of individuals between patches is modelled as both a constant rate, and a function which is increasing with population density. Finally, we discuss the 'optimal' control strategy in this context. We find that, whilst a population harvested from a coupled system is able to produce an inflated yield, this coupling can also cause the population to be more resistant to higher harvesting efforts, increasing the effort required to drive the population to extinction. Spatial perturbation raises this extinction threshold further still, providing a survival mechanism not only for the individuals that avoid being killed, but for the population as a whole. With regards to the eradication of disease, we show that disturbance may either raise or lower the pathogen exclusion threshold depending on the particular characteristics of the pathogen. In certain cases, we have shown that spatial perturbation may force a population to be susceptible to an infectious invasion where its natural carrying capacity would prevent this.

Mark-recapture methods use repeated captures of individually identifiable animals to provide estimates of properties of populations. Different models allow estimates to be obtained for population size and rates of processes governing population dynamics. State-space models consist of two linked processes evolving simultaneously over time. The state process models the evolution of the true, but unknown, states of the population. The observation process relates observations on the population to these true states. Mark-recapture models specified within a state-space framework allow population dynamics models to be embedded in inference ensuring that estimated changes in the population are consistent with assumptions regarding the biology of the modelled population. This overcomes a limitation of current mark-recapture methods. Two alternative approaches are considered. The "conditional" approach conditions on known numbers of animals possessing capture history patterns including capture in the current time period. An animal's capture history determines its state; consequently, capture parameters appear in the state process rather than the observation process. There is no observation error in the model. Uncertainty occurs only through the numbers of animals not captured in the current time period. An "unconditional" approach is considered in which the capture histories are regarded as observations. Consequently, capture histories do not influence an animal's state and capture probability parameters appear in the observation process. Capture histories are considered a random realization of the stochastic observation process. This is more consistent with traditional mark-recapture methods. Development and implementation of particle filtering techniques for fitting these models under each approach are discussed. Simulation studies show reasonable performance for the unconditional approach and highlight problems with the conditional approach. Strengths and limitations of each approach are outlined, with reference to Soay sheep data analysis, and suggestions are presented for future analyses.

El gecko, Phyllodactylus sentosus, es endémico del Perú y el único miembro de la Familia Phyllodactylidae considerado amenazado por las leyes peruanas. Se conoce su distribución principalmente por subpoblaciones en siete sitios arqueológicos, aislados entre sí, dentro de la ciudad de Lima. Se analizó la dinámica y estructura poblacional de P. sentosus en la Huaca Pucllana, ubicada en el distrito de Miraflores, Lima, a través de evaluaciones mensuales de captura y recaptura. Se marcaron, midieron e identificaron hembras, machos y juveniles. La población varió estacionalmente y la estructura por clases de tamaño no siguió una distribución normal, la mayor parte de los organismos fueron juveniles y se distribuyeron en las clases de menor tamaño, los adultos presentaron una mayor dispersión y en todos los meses evaluados se registraron hembras, machos y juveniles. Las hembras fueron significativamente más grandes que los machos, por lo que existe dimorfismo sexual de tamaño. La temporada de reproducción fue de noviembre a febrero y de febrero a marzo se dieron la mayor cantidad de nacimientos. P. sentosus mostró una proporción de sexual de 1(♀) : 0,9(♂). Los resultados de este estudio muestran aspectos importantes sobre la historia de vida de P. sentosus, proveyendo información útil para la toma de decisiones sobre el manejo y conservación de esta especie amenazada.The gecko, Phyllodactylus sentosus, is endemic to Peru and is the only member of the family Phyllodactylidae which is deemed threatened under the Peruvian legislation. Its distribution is mainly known in the form of subpopulations in seven separate archaeological sites, not connected with one another, within the city of Lima. The population dynamics and structure of P. sentosus were analyzed in the Huaca Pucllana, a pre-Incan temple, located in the Miraflores district in Lima. The analysis comprised monthly assessments of capture and recapture. Female, male and juvenile geckos were marked, measured and identified. The population varied on a seasonal basis and the size class structure did not follow a normal distribution. Most organisms were juvenile and distributed into the lower size classes. The adults presented a greater spread. Throughout the months of the assessment, females, males and juvenile geckos were recorded. The females were significantly larger than males. Therefore, there is sexual dimorphism in size. The mating season occurred from November through February and most births took place from February through March. P. sentosus showed a sex rate of 1(♀) : 0,9(♂). The results of this study feature important aspects in regard to the life history of P. sentosus, providing useful information for the decision making about the management and conservation of this threatened species.

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