Quantifying invasion resistance: the use of recruitment functions to control for propagule pressure

Invasive species distributions tend to be biased towards some habitats compared to others due to the combined effects of habitat-specific resistance to invasion and non-uniform propagule pressure. These two factors may also interact, with habitat resistance varying as a function of propagule supply rate. Recruitment experiments, in which the number of individuals recruiting into a population is measured under different propagule supply rates, can help us understand these interactions and quantify habitat resistance to invasion while controlling for variation in propagule supply rate. Here, we constructed recruitment functions for the invasive herb Hieracium lepidulum by sowing seeds at five different densities into six different habitat types in New Zealand's Southern Alps repeated over two successive years, and monitored seedling recruitment and survival over a four year period. We fitted recruitment functions that allowed us to estimate the total number of safe sites available for plants to occupy, which we used as a measure of invasion resistance, and tested several hypotheses concerning how invasion resistance differed among habitats and over time. We found significant differences in levels of H. lepidulum recruitment among habitats, which did not match the species' current distribution in the landscape. Local biotic and abiotic characteristics helped explain some of the between-habitat variation, with vascular plant species richness, vascular plant cover, and light availability, all positively correlated with the number of safe sites for recruitment. Resistance also varied over time however, with cohorts sown in successive years showing different levels of recruitment in some habitats but not others. These results show that recruitment functions can be used to quantify habitat resistance to invasion and to identify potential mechanisms of invasion resistance

An investigation of dendritic delay in octopus cells of the mammalian cochlear nucleus

Octopus cells, located in the mammalian auditory brainstem, receive their excitatory synaptic input exclusively from auditory nerve fibers (ANFs). They respond with accurately timed spikes but are broadly tuned for sound frequency. Since the representation of information in the auditory nerve is well understood, it is possible to pose a number of questions about the relationship between the intrinsic electrophysiology, dendritic morphology, synaptic connectivity, and the ultimate functional role of octopus cells in the brainstem. This study employed a multi-compartmental Hodgkin-Huxley model to determine whether dendritic delay in octopus cells improves synaptic input coincidence detection in octopus cells by compensating for the cochlear traveling wave delay. The propagation time of post-synaptic potentials from synapse to soma was investigated. We found that the total dendritic delay was approximately 0.275 ms. It was observed that low-threshold potassium channels in the dendrites reduce the amplitude dependence of the dendritic delay of post-synaptic potentials. As our hypothesis predicted, the model was most sensitive to acoustic onset events, such as the glottal pulses in speech when the synaptic inputs were arranged such that the model's dendritic delay compensated for the cochlear traveling wave delay across the ANFs. The range of sound frequency input from ANFs was also investigated. The results suggested that input to octopus cells is dominated by high frequency ANFs

The effect of morphology upon electrophysiological responses of retinal ganglion cells: simulation results

Retinal ganglion cells (RGCs) display differences in their morphology and intrinsic electrophysiology. The goal of this study is to characterize the ionic currents that explain the behavior of ON and OFF RGCs and to explore if all morphological types of RGCs exhibit the phenomena described in electrophysiological data. We extend our previous single compartment cell models of ON and OFF RGCs to more biophysically realistic multicompartment cell models and investigate the effect of cell morphology on intrinsic electrophysiological properties. The membrane dynamics are described using the Hodgkin - Huxley type formalism. A subset of published patch-clamp data from isolated intact mouse retina is used to constrain the model and another subset is used to validate the model. Two hundred morphologically distinct ON and OFF RGCs are simulated with various densities of ionic currents in different morphological neuron compartments. Our model predicts that the differences between ON and OFF cells are explained by the presence of the low voltage activated calcium current in OFF cells and absence of such in ON cells. Our study shows through simulation that particular morphological types of RGCs are capable of exhibiting the full range of phenomena described in recent experiments. Comparisons of outputs from different cells indicate that the RGC morphologies that best describe recent experimental results are ones that have a larger ratio of soma to total surface area

Invasion success and impacts of Hieracium lepidulum in a New Zealand tussock grassland and montane forest

Invasive species represent a major concern; they can result in serious ecological and economic losses and are recognised as one of the most serious threats to global species diversity. Plant invasions are of particular concern in New Zealand, which has high proportions of both naturalised and endemic plant species. In this thesis I focussed on the invasive plant Hieracium lepidulum, an exotic weed introduced from Europe to New Zealand prior to 1941. It is invasive in a variety of habitats in the South Island, where it has steadily increased in distribution and abundance over the last 50 years, and is thought to have detrimental impacts on native plant communities. I investigated factors influencing its invasion success and tested for impacts on native plant communities, making extensive use of existing plots into which H. lepidulum was experimentally introduced in 2003. I examined how community richness, turnover, resource availability and propagule pressure of the invader interacted to determine the invasion success of H. lepidulum. Results differed markedly above and below treeline. Above treeline, plots with higher richness and turnover were more invaded; below treeline, plots with higher available light were more invaded. In both habitats, these findings were modified by the influence of propagule pressure; at low propagule pressure, site characteristics were non-significant in explaining invasion success, while at higher propagule pressure these effects became significant. To test for impacts resulting in altered community composition and structure, I looked for changes in community richness, diversity and evenness subsequent to H. lepidulum introduction. As impacts may be more apparent at fine spatial scales, I made measurements at a 5 x 5 cm cell scale in addition to the established 30 x 30 cm plot scale. Plot species richness increased from 2003 to 2009 and a component of this increase was associated with H. lepidulum density. Other relationships between the plant community and H. lepidulum were generally non-significant. Results showed that H. lepidulum has had no negative effects on community richness, evenness or diversity. Despite being able to opportunistically colonise grassland sites with high turnover, and forest sites subject to canopy disturbance, dependant on propagule pressure, it appears H. lepidulum has not impacted community composition or structure

Eigenvalue spectral properties of sparse random matrices obeying Dale's law

Understanding the dynamics of large networks of neurons with heterogeneous connectivity architectures is a complex physics problem that demands novel mathematical techniques. Biological neural networks are inherently spatially heterogeneous, making them difficult to mathematically model. Random recurrent neural networks capture complex network connectivity structures and enable mathematically tractability. Our paper generalises previous classical results to sparse connectivity matrices which have distinct excitatory (E) or inhibitory (I) neural populations. By investigating sparse networks we construct our analysis to examine the impacts of all levels of network sparseness, and discover a novel nonlinear interaction between the connectivity matrix and resulting network dynamics, in both the balanced and unbalanced cases. Specifically, we deduce new mathematical dependencies describing the influence of sparsity and distinct E/I distributions on the distribution of eigenvalues (eigenspectrum) of the networked Jacobian. Furthermore, we illustrate that the previous classical results are special cases of the more general results we have described here. Understanding the impacts of sparse connectivities on network dynamics is of particular importance for both theoretical neuroscience and mathematical physics as it pertains to the structure-function relationship of networked systems and their dynamics. Our results are an important step towards developing analysis techniques that are essential to studying the impacts of larger scale network connectivity on network function, and furthering our understanding of brain function and dysfunction.Comment: 18 pages, 6 figure

Enantioselective Disposition of 2-Aryipropionic Acid Nonsteroidal Anti-Inflam matory Drugs . IV . Ketoprofen Disposition1

ABSTRACT The disposition of ketoprofen enantiomers has been studied in 1 2 rabbits with normal renal function (control) and in 6 of these rabbits with renal dysfunction. In control animals a mean (S.E.M.) of 0.09 (0.01) of R-ketoprofen was inverted to its S-enantiomer. The mean distribution volumes for A-and S-ketoprofen were 114 (7.4) and 29

Soft-bound synaptic plasticity increases storage capacity

Accurate models of synaptic plasticity are essential to understand the adaptive properties of the nervous system and for realistic models of learning and memory. Experiments have shown that synaptic plasticity depends not only on pre- and post-synaptic activity patterns, but also on the strength of the connection itself. Namely, weaker synapses are more easily strengthened than already strong ones. This so called soft-bound plasticity automatically constrains the synaptic strengths. It is known that this has important consequences for the dynamics of plasticity and the synaptic weight distribution, but its impact on information storage is unknown. In this modeling study we introduce an information theoretic framework to analyse memory storage in an online learning setting. We show that soft-bound plasticity increases a variety of performance criteria by about 18% over hard-bound plasticity, and likely maximizes the storage capacity of synapses

Enantioselective Disposition of 2-Aryipropionic Acid Nonsteroidal Anti-Inflammatory Drugs. Ill. Fenoprofen Disposition'

ABSTRACT The formation of the acylglucuronides of clofibric acid (Odum and Orton, 1983) and diflunisal (Faed et al., 1984) has also been reported to be induced by phenobarbital. Based on the above observations we have examined the effect ofphenobarbital on fenoprofen disposition and its enantiomeric consequences. ABBREVIATIONS: Cl5