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Description
Amongst the most studied of the social insects, the honey bee has a prominent place due to its economic importance and influence on human societies. Honey bee colonies can have over 50,000 individuals, whose activities are coordinated by chemical signals called pheromones. Because these pheromones are secreted from various exocrine glands, the proper development and function of these glands are vital to colony dynamics. In this thesis, I present a study of the developmental ontogeny of the exocrine glands found in the head of the honey bee. In Chapter 2, I elucidate how the larval salivary gland transitions to an adult salivary gland through apoptosis and cell growth, differentiation and migration. I also explain the development of the hypopharyngeal and the mandibular gland using apoptotic markers and cytoskeletal markers like tubulin and actin. I explain the fundamental developmental plan for the formation of the glands and show that apoptosis plays an important role in the transformation toward an adult gland.
ContributorsNath, Rachna (Author) / Gadau, Juergen (Thesis advisor) / Rawls, Alan (Committee member) / Harrison, Jon (Committee member) / Arizona State University (Publisher)
Created2018
Description
Two urban flows are analyzed, one concerned with pollutant transport in a Phoenix, Arizona neighborhood and the other with windshear detection at the Hong Kong International Airport (HKIA).
Lagrangian measures, identified with finite-time Lyapunov exponents, are first used to characterize transport patterns of inertial pollutant particles. Motivated by actual events the focus is on flows in realistic urban geometry. Both deterministic and stochastic transport patterns are identified, as inertial Lagrangian coherent structures. For the deterministic case, the organizing structures are well defined and are extracted at different hours of a day to reveal the variability of coherent patterns. For the stochastic case, a random displacement model for fluid particles is formulated, and used to derive the governing equations for inertial particles to examine the change in organizing structures due to ``zeroth-order'' random noise. It is found that, (1) the Langevin equation for inertial particles can be reduced to a random displacement model; (2) using random noise based on inhomogeneous turbulence, whose diffusivity is derived from $k$-$\epsilon$ models, major coherent structures survive to organize local flow patterns and weaker structures are smoothed out due to random motion.
A study of three-dimensional Lagrangian coherent structures (LCS) near HKIA is then presented and related to previous developments of two-dimensional (2D) LCS analyses in detecting windshear experienced by landing aircraft. The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the lidar scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. It is found that, while the three models and the LIDAR do recover similar features of the windshear experienced by a landing aircraft (along the landing trajectory), their Lagrangian signatures over the entire domain are quite different - a portion of each numerical model captures certain features resembling those LCS extracted from independent 2D LIDAR analyses based on observations. Overall, it was found that the Weather Research and Forecast (WRF) model provides the best agreement with the LIDAR data.
Finally, the three-dimensional variational (3DVAR) data assimilation scheme in WRF is used to incorporate the LIDAR line of sight velocity observations into the WRF model forecast at HKIA. Using two different days as test cases, it is found that the LIDAR data can be successfully and consistently assimilated into WRF. Using the updated model forecast LCS are extracted along the LIDAR scanning cone and compare to onboard flight data. It is found that the LCS generated from the updated WRF forecasts are generally better correlated with the windshear experienced by landing aircraft as compared to the LIDAR extracted LCS alone, which suggests that such a data assimilation scheme could be used for the prediction of windshear events.
Lagrangian measures, identified with finite-time Lyapunov exponents, are first used to characterize transport patterns of inertial pollutant particles. Motivated by actual events the focus is on flows in realistic urban geometry. Both deterministic and stochastic transport patterns are identified, as inertial Lagrangian coherent structures. For the deterministic case, the organizing structures are well defined and are extracted at different hours of a day to reveal the variability of coherent patterns. For the stochastic case, a random displacement model for fluid particles is formulated, and used to derive the governing equations for inertial particles to examine the change in organizing structures due to ``zeroth-order'' random noise. It is found that, (1) the Langevin equation for inertial particles can be reduced to a random displacement model; (2) using random noise based on inhomogeneous turbulence, whose diffusivity is derived from $k$-$\epsilon$ models, major coherent structures survive to organize local flow patterns and weaker structures are smoothed out due to random motion.
A study of three-dimensional Lagrangian coherent structures (LCS) near HKIA is then presented and related to previous developments of two-dimensional (2D) LCS analyses in detecting windshear experienced by landing aircraft. The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the lidar scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. It is found that, while the three models and the LIDAR do recover similar features of the windshear experienced by a landing aircraft (along the landing trajectory), their Lagrangian signatures over the entire domain are quite different - a portion of each numerical model captures certain features resembling those LCS extracted from independent 2D LIDAR analyses based on observations. Overall, it was found that the Weather Research and Forecast (WRF) model provides the best agreement with the LIDAR data.
Finally, the three-dimensional variational (3DVAR) data assimilation scheme in WRF is used to incorporate the LIDAR line of sight velocity observations into the WRF model forecast at HKIA. Using two different days as test cases, it is found that the LIDAR data can be successfully and consistently assimilated into WRF. Using the updated model forecast LCS are extracted along the LIDAR scanning cone and compare to onboard flight data. It is found that the LCS generated from the updated WRF forecasts are generally better correlated with the windshear experienced by landing aircraft as compared to the LIDAR extracted LCS alone, which suggests that such a data assimilation scheme could be used for the prediction of windshear events.
ContributorsKnutson, Brent (Author) / Tang, Wenbo (Thesis advisor) / Calhoun, Ronald (Committee member) / Huang, Huei-Ping (Committee member) / Kostelich, Eric (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2018
Description
The role of environmental factors that influence atmospheric propagation of sound originating from freeway noise sources is studied with a combination of field experiments and numerical simulations. Acoustic propagation models are developed and adapted for refractive index depending upon meteorological conditions. A high-resolution multi-nested environmental forecasting model forced by coarse global analysis is applied to predict real meteorological profiles at fine scales. These profiles are then used as input for the acoustic models. Numerical methods for producing higher resolution acoustic refractive index fields are proposed. These include spatial and temporal nested meteorological simulations with vertical grid refinement. It is shown that vertical nesting can improve the prediction of finer structures in near-ground temperature and velocity profiles, such as morning temperature inversions and low level jet-like features. Accurate representation of these features is shown to be important for modeling sound refraction phenomena and for enabling accurate noise assessment. Comparisons are made using the acoustic model for predictions with profiles derived from meteorological simulations and from field experiment observations in Phoenix, Arizona. The challenges faced in simulating accurate meteorological profiles at high resolution for sound propagation applications are highlighted and areas for possible improvement are discussed.
A detailed evaluation of the environmental forecast is conducted by investigating the Surface Energy Balance (SEB) obtained from observations made with an eddy-covariance flux tower compared with SEB from simulations using several physical parameterizations of urban effects and planetary boundary layer schemes. Diurnal variation in SEB constituent fluxes are examined in relation to surface layer stability and modeled diagnostic variables. Improvement is found when adapting parameterizations for Phoenix with reduced errors in the SEB components. Finer model resolution (to 333 m) is seen to have insignificant ($<1\sigma$) influence on mean absolute percent difference of 30-minute diurnal mean SEB terms. A new method of representing inhomogeneous urban development density derived from observations of impervious surfaces with sub-grid scale resolution is then proposed for mesoscale applications. This method was implemented and evaluated within the environmental modeling framework. Finally, a new semi-implicit scheme based on Leapfrog and a fourth-order implicit time-filter is developed.
A detailed evaluation of the environmental forecast is conducted by investigating the Surface Energy Balance (SEB) obtained from observations made with an eddy-covariance flux tower compared with SEB from simulations using several physical parameterizations of urban effects and planetary boundary layer schemes. Diurnal variation in SEB constituent fluxes are examined in relation to surface layer stability and modeled diagnostic variables. Improvement is found when adapting parameterizations for Phoenix with reduced errors in the SEB components. Finer model resolution (to 333 m) is seen to have insignificant ($<1\sigma$) influence on mean absolute percent difference of 30-minute diurnal mean SEB terms. A new method of representing inhomogeneous urban development density derived from observations of impervious surfaces with sub-grid scale resolution is then proposed for mesoscale applications. This method was implemented and evaluated within the environmental modeling framework. Finally, a new semi-implicit scheme based on Leapfrog and a fourth-order implicit time-filter is developed.
ContributorsShaffer, Stephen R. (Author) / Moustaoui, Mohamed (Thesis advisor) / Mahalov, Alex (Committee member) / Fernando, Harindra J.S. (Committee member) / Ovenden, Nicholas C. (Committee member) / Huang, Huei-Ping (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2014
Description
During the 1960s, the long-standing idea that traits or behaviors could be
explained by natural selection acting on traits that persisted "for the good of the group" prompted a series of debates about group-level selection and the effectiveness with which natural selection could act at or across multiple levels of biological organization. For some this topic remains contentious, while others consider the debate settled, even while disagreeing about when and how resolution occurred, raising the question: "Why have these debates continued?"
Here I explore the biology, history, and philosophy of the possibility of natural selection operating at levels of biological organization other than the organism by focusing on debates about group-level selection that have occurred since the 1960s. In particular, I use experimental, historical, and synthetic methods to review how the debates have changed, and whether different uses of the same words and concepts can lead to different interpretations of the same experimental data.
I begin with the results of a group-selection experiment I conducted using the parasitoid wasp Nasonia, and discuss how the interpretation depends on how one conceives of and defines a "group." Then I review the history of the group selection controversy and argue that this history is best interpreted as multiple, interrelated debates rather than a single continuous debate. Furthermore, I show how the aspects of these debates that have changed the most are related to theoretical content and empirical data, while disputes related to methods remain largely unchanged. Synthesizing this material, I distinguish four different "approaches" to the study of multilevel selection based on the questions and methods used by researchers, and I use the results of the Nasonia experiment to discuss how each approach can lead to different interpretations of the same experimental data. I argue that this realization can help to explain why debates about group and multilevel selection have persisted for nearly sixty years. Finally, the conclusions of this dissertation apply beyond evolutionary biology by providing an illustration of how key concepts can change over time, and how failing to appreciate this fact can lead to ongoing controversy within a scientific field.
explained by natural selection acting on traits that persisted "for the good of the group" prompted a series of debates about group-level selection and the effectiveness with which natural selection could act at or across multiple levels of biological organization. For some this topic remains contentious, while others consider the debate settled, even while disagreeing about when and how resolution occurred, raising the question: "Why have these debates continued?"
Here I explore the biology, history, and philosophy of the possibility of natural selection operating at levels of biological organization other than the organism by focusing on debates about group-level selection that have occurred since the 1960s. In particular, I use experimental, historical, and synthetic methods to review how the debates have changed, and whether different uses of the same words and concepts can lead to different interpretations of the same experimental data.
I begin with the results of a group-selection experiment I conducted using the parasitoid wasp Nasonia, and discuss how the interpretation depends on how one conceives of and defines a "group." Then I review the history of the group selection controversy and argue that this history is best interpreted as multiple, interrelated debates rather than a single continuous debate. Furthermore, I show how the aspects of these debates that have changed the most are related to theoretical content and empirical data, while disputes related to methods remain largely unchanged. Synthesizing this material, I distinguish four different "approaches" to the study of multilevel selection based on the questions and methods used by researchers, and I use the results of the Nasonia experiment to discuss how each approach can lead to different interpretations of the same experimental data. I argue that this realization can help to explain why debates about group and multilevel selection have persisted for nearly sixty years. Finally, the conclusions of this dissertation apply beyond evolutionary biology by providing an illustration of how key concepts can change over time, and how failing to appreciate this fact can lead to ongoing controversy within a scientific field.
ContributorsDimond, Christopher C (Author) / Collins, James P. (Thesis advisor) / Gadau, Juergen (Committee member) / Laubichler, Manfred (Committee member) / Armendt, Brad (Committee member) / Lynch, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
For interspecific mutualisms, the behavior of one partner can influence the fitness of the other, especially in the case of symbiotic mutualisms where partners live in close physical association for much of their lives. Behavioral effects on fitness may be particularly important if either species in these long-term relationships displays personality. Animal personality is defined as repeatable individual differences in behavior, and how correlations among these consistent traits are structured is termed behavioral syndromes. Animal personality has been broadly documented across the animal kingdom but is poorly understood in the context of mutualisms. My dissertation focuses on the structure, causes, and consequences of collective personality in Azteca constructor colonies that live in Cecropia trees, one of the most successful and prominent mutualisms of the neotropics. These pioneer plants provide hollow internodes for nesting and nutrient-rich food bodies; in return, the ants provide protection from herbivores and encroaching vines. I first explored the structure of the behavioral syndrome by testing the consistency and correlation of colony-level behavioral traits under natural conditions in the field. Traits were both consistent within colonies and correlated among colonies revealing a behavioral syndrome along a docile-aggressive axis. Host plants of more active, aggressive colonies had less leaf damage, suggesting a link between a colony personality and host plant health. I then studied how aspects of colony sociometry are intertwined with their host plants by assessing the relationship among plant growth, colony growth, colony structure, ant morphology, and colony personality. Colony personality was independent of host plant measures like tree size, age, volume. Finally, I tested how colony personality influenced by soil nutrients by assessing personality in the field and transferring colonies to plants the greenhouse under different soil nutrient treatments. Personality was correlated with soil nutrients in the field but was not influenced by soil nutrient treatment in the greenhouse. This suggests that soil nutrients interact with other factors in the environment to structure personality. This dissertation demonstrates that colony personality is an ecologically relevant phenomenon and an important consideration for mutualism dynamics.
ContributorsMarting, Peter (Author) / Pratt, Stephen C (Thesis advisor) / Wcislo, William T (Committee member) / Hoelldobler, Bert (Committee member) / Fewell, Jennifer H (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2018
Description
The tools developed for the use of investigating dynamical systems have provided critical understanding to a wide range of physical phenomena. Here these tools are used to gain further insight into scalar transport, and how it is affected by mixing. The aim of this research is to investigate the efficiency of several different partitioning methods which demarcate flow fields into dynamically distinct regions, and the correlation of finite-time statistics from the advection-diffusion equation to these regions.
For autonomous systems, invariant manifold theory can be used to separate the system into dynamically distinct regions. Despite there being no equivalent method for nonautonomous systems, a similar analysis can be done. Systems with general time dependencies must resort to using finite-time transport barriers for partitioning; these barriers are the edges of Lagrangian coherent structures (LCS), the analog to the stable and unstable manifolds of invariant manifold theory. Using the coherent structures of a flow to analyze the statistics of trapping, flight, and residence times, the signature of anomalous diffusion are obtained.
This research also investigates the use of linear models for approximating the elements of the covariance matrix of nonlinear flows, and then applying the covariance matrix approximation over coherent regions. The first and second-order moments can be used to fully describe an ensemble evolution in linear systems, however there is no direct method for nonlinear systems. The problem is only compounded by the fact that the moments for nonlinear flows typically don't have analytic representations, therefore direct numerical simulations would be needed to obtain the moments throughout the domain. To circumvent these many computations, the nonlinear system is approximated as many linear systems for which analytic expressions for the moments exist. The parameters introduced in the linear models are obtained locally from the nonlinear deformation tensor.
For autonomous systems, invariant manifold theory can be used to separate the system into dynamically distinct regions. Despite there being no equivalent method for nonautonomous systems, a similar analysis can be done. Systems with general time dependencies must resort to using finite-time transport barriers for partitioning; these barriers are the edges of Lagrangian coherent structures (LCS), the analog to the stable and unstable manifolds of invariant manifold theory. Using the coherent structures of a flow to analyze the statistics of trapping, flight, and residence times, the signature of anomalous diffusion are obtained.
This research also investigates the use of linear models for approximating the elements of the covariance matrix of nonlinear flows, and then applying the covariance matrix approximation over coherent regions. The first and second-order moments can be used to fully describe an ensemble evolution in linear systems, however there is no direct method for nonlinear systems. The problem is only compounded by the fact that the moments for nonlinear flows typically don't have analytic representations, therefore direct numerical simulations would be needed to obtain the moments throughout the domain. To circumvent these many computations, the nonlinear system is approximated as many linear systems for which analytic expressions for the moments exist. The parameters introduced in the linear models are obtained locally from the nonlinear deformation tensor.
ContributorsWalker, Phillip (Author) / Tang, Wenbo (Thesis advisor) / Kostelich, Eric (Committee member) / Mahalov, Alex (Committee member) / Moustaoui, Mohamed (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2018
Description
An important component of insect social structure is the number of queens that cohabitate in a colony. Queen number is highly variable between and within species. It can begin at colony initiation when often unrelated queens form cooperative social groups, a strategy known as primary polygyny. The non-kin cooperative groups formed by primary polygyny have profound effects on the social dynamics and inclusive fitness benefits within a colony. Despite this, the evolution of non-kin queen cooperation has been relatively overlooked in considerations of the evolution of cooperative sociality. To date, studies examining the costs and benefits of primary polygyny have focused primarily on the advantages of multiple queens during colony founding and early growth, but the impact of their presence extends to colony maturity and reproduction.
In this dissertation, I evaluate the ecological drivers and fitness consequences of non-kin queen cooperation, by comparing the reproduction of mature single-queen versus polygynous harvester ant (Pogonomyrmex californicus) colonies in the field. I captured and quantified the total number and biomass of reproductives across multiple mating seasons, comparing between populations that vary in the proportion of single queen versus polygynous colonies, to assess the fitness outcomes of queen cooperation. Colonies in a mainly polygynous site had lower reproductive investment than those in sites with predominantly single-queen colonies. The site dominated by polygyny had higher colony density and displayed evidence of resource limitation, pressures that may drive the evolution of queen cooperation.
I also used microsatellite markers to examine how polygynous queens share worker and reproductive production with nest-mate queens. The majority of queens fairly contribute to worker production and equally share reproductive output. However, there is a low frequency of queens that under-produce workers and over-produce reproductive offspring. This suggests that cheating by reproducing queens is possible, but uncommon. Competitive pressure from neighboring colonies could reduce the success of colonies that contain cheaters and maintain a low frequency of this phenotype in the population.
In this dissertation, I evaluate the ecological drivers and fitness consequences of non-kin queen cooperation, by comparing the reproduction of mature single-queen versus polygynous harvester ant (Pogonomyrmex californicus) colonies in the field. I captured and quantified the total number and biomass of reproductives across multiple mating seasons, comparing between populations that vary in the proportion of single queen versus polygynous colonies, to assess the fitness outcomes of queen cooperation. Colonies in a mainly polygynous site had lower reproductive investment than those in sites with predominantly single-queen colonies. The site dominated by polygyny had higher colony density and displayed evidence of resource limitation, pressures that may drive the evolution of queen cooperation.
I also used microsatellite markers to examine how polygynous queens share worker and reproductive production with nest-mate queens. The majority of queens fairly contribute to worker production and equally share reproductive output. However, there is a low frequency of queens that under-produce workers and over-produce reproductive offspring. This suggests that cheating by reproducing queens is possible, but uncommon. Competitive pressure from neighboring colonies could reduce the success of colonies that contain cheaters and maintain a low frequency of this phenotype in the population.
ContributorsHaney, Brian R (Author) / Fewell, Jennifer H (Thesis advisor) / Cole, Blaine J. (Committee member) / Gadau, Juergen (Committee member) / Hoelldobler, Bert (Committee member) / Rutowski, Ron L (Committee member) / Arizona State University (Publisher)
Created2017
Description
Efforts to treat prostate cancer have seen an uptick, as the world’s most commoncancer in men continues to have increasing global incidence. Clinically, metastatic
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
ContributorsReckell, Trevor (Author) / Kostelich, Eric (Thesis advisor) / Kuang, Yang (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2020
Description
The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations O3 due to urbanization within cities in arid/semi-arid environments. First, a method based on a shape preserving Monotonic Cubic Interpolation (MCI) is developed and used to downscale anthropogenic emissions from the 4 km resolution 2005 National Emissions Inventory (NEI05) to the finest model resolution of 1 km. Using the rapidly expanding Phoenix metropolitan region as the area of focus, we demonstrate the proposed MCI method achieves ozone simulation results with appreciably improved correspondence to observations relative to the default interpolation method of the WRF-Chem system. Next, two additional sets of experiments are conducted, with the recommended MCI approach, to examine impacts of urbanization on ozone production: (1) the urban land cover is included (i.e., urbanization experiments) and, (2) the urban land cover is replaced with the region's native shrubland. Impacts due to the presence of the built environment on O3 are highly heterogeneous across the metropolitan area. Increased near surface O3 due to urbanization of 10–20 ppb is predominantly a nighttime phenomenon while simulated impacts during daytime are negligible. Urbanization narrows the daily O3 range (by virtue of increasing nighttime minima), an impact largely due to the region's urban heat island. Our results demonstrate the importance of the MCI method for accurate representation of the diurnal profile of ozone, and highlight its utility for high-resolution air quality simulations for urban areas.
ContributorsLi, Jialun (Author) / Georgescu, Matei (Author) / Hyde, Peter (Author) / Mahalov, Alex (Author) / Moustaoui, Mohamed (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2014-11-01
Description
Adaptation requires genetic variation, but founder populations are generally genetically depleted. Here we sequence two populations of an inbred ant that diverge in phenotype to determine how variability is generated. Cardiocondyla obscurior has the smallest of the sequenced ant genomes and its structure suggests a fundamental role of transposable elements (TEs) in adaptive evolution. Accumulations of TEs (TE islands) comprising 7.18% of the genome evolve faster than other regions with regard to single-nucleotide variants, gene/exon duplications and deletions and gene homology. A non-random distribution of gene families, larvae/adult specific gene expression and signs of differential methylation in TE islands indicate intragenomic differences in regulation, evolutionary rates and coalescent effective population size. Our study reveals a tripartite interplay between TEs, life history and adaptation in an invasive species.
ContributorsSchrader, Lukas (Author) / Kim, Jay W. (Author) / Ence, Daniel (Author) / Zimin, Aleksey (Author) / Klein, Antonia (Author) / Wyschetzki, Katharina (Author) / Weichselgartner, Tobias (Author) / Kemena, Carsten (Author) / Stoekl, Johannes (Author) / Schultner, Eva (Author) / Wurm, Yannick (Author) / Smith, Christopher D. (Author) / Yandell, Mark (Author) / Heinze, Juergen (Author) / Gadau, Juergen (Author) / Oettler, Jan (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-12-01