What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.     

A stream by any other name: does β-diversity differ between Nearctic and Neotropical streams?

Hydrobiologia - Beta diversity typically increases with decreasing latitude, with explanations of this pattern often based on tropical origins of most clades. Black flies (Diptera: Simuliidae) are...     

Comparative assessment of the intracellular survival of the Burkholderia pseudomallei bopC mutant

Burkholderia pseudomallei, the causative agent of melioidosis, is a Gram-negative saprophytic bacterium capable of surviving within phagocytic cells. To assess the role of BopC (a type III secreted effector protein) in the pathogenesis of B. pseudomallei, a B. pseudomallei bopC mutant was used to infect J774A.1 macrophage-like cells. The bopC mutant showed significantly reduced intracellular survival in infected macrophages compared to wild-type B. pseudomallei. In addition, the bopC mutant displayed delayed escape from endocytic vesicles compared with the wild-type strain. This indicates that BopC is important, and at least in part, needed for intracellular survival of B. pseudomallei.     

The Viral Chemokine MCK-2 of Murine Cytomegalovirus Promotes Infection as Part of a gH/gL/MCK-2 Complex

Human cytomegalovirus (HCMV) forms two gH/gL glycoprotein complexes, gH/gL/gO and gH/gL/pUL(128,130,131A), which determine the tropism, the entry pathways and the mode of spread of the virus. For murine cytomegalovirus (MCMV), which serves as a model for HCMV, a gH/gL/gO complex functionally homologous to the HCMV gH/gL/gO complex has been described. Knock-out of MCMV gO does impair, but not abolish, virus spread indicating that also MCMV might form an alternative gH/gL complex. Here, we show that the MCMV CC chemokine MCK-2 forms a complex with the glycoprotein gH, a complex which is incorporated into the virion. We could additionally show that mutants lacking both, gO and MCK-2 are not able to produce infectious virus. Trans-complementation of these double mutants with either gO or MCK-2 showed that both proteins can promote infection of host cells, although through different entry pathways. MCK-2 has been extensively studied in vivo by others. It has been shown to be involved in attracting cells for virus dissemination and in regulating antiviral host responses. We now show that MCK-2, by forming a complex with gH, strongly promotes infection of macrophages in vitro and in vivo. Thus, MCK-2 may play a dual role in MCMV infection, as a chemokine regulating the host response and attracting specific target cells and as part of a glycoprotein complex promoting entry into cells crucial for virus dissemination.     

Identification of Pauses during Formation of HIV-1 Virus Like Particles

HIV Gag polymerizes on the plasma membrane to form virus like particles (VLPs) that have similar diameters to wild-type viruses. We use multicolor, dual-penetration depth, total internal reflection fluorescence microscopy, which corrects for azimuthal movement, to image the assembly of individual VLPs from the time of nucleation to the recruitment of VPS4 (a component of the endosomal sorting complexes required for transport, and which marks the final stage of VLP assembly). Using a mathematical model for assembly and maximum-likelihood comparison of fits both with and without pauses, we detect pauses during Gag polymerization in 60% of VLPs. Pauses range from 2 to 20 min, with an exponentially distributed duration that is independent of cytosolic Gag concentration. VLPs assembled with late domain mutants of Gag (which do not recruit the key endosomal sorting complexes required for transport proteins Alix or TSG101) exhibit similar pause distributions. These pauses indicate that a single rate-limiting event is required for continuation of assembly. We suggest that pauses are either related to incorporation of defects in the hexagonal Gag lattice during VLP assembly or are caused by shortcomings in interactions of Gag with essential and still undefined cellular components during formation of curvature on the plasma membrane.     

Scorpion toxins for the reversal of BoNT-induced paralysis

The botulinum neurotoxins, characterized by their neuromuscular paralytic effects, are the most toxic proteins known to man. Due to their extreme potency, ease of production, and duration of activity, the BoNT proteins have been classified by the Centers for Disease Control as high threat agents for bioterrorism. In an attempt to discover effective BoNT therapeutics, we have pursued a strategy in which we leverage the blockade of K⁺ channels that ultimately results in the reversal of neuromuscular paralysis. Towards this end, we utilized peptides derived from scorpion venom that are highly potent K⁺ channel blockers. Herein, we report the synthesis of charybdotoxin, a 37 amino acid peptide, and detail its activity, along with iberiotoxin and margatoxin, in a mouse phrenic nerve hemidiaphragm assay in the absence and the presence of BoNT/A.     

A hierarchical nest survival model integrating incomplete temporally varying covariates

Nest success is a critical determinant of the dynamics of avian populations, and nest survival modeling has played a key role in advancing avian ecology and management. Beginning with the development of daily nest survival models, and proceeding through subsequent extensions, the capacity for modeling the effects of hypothesized factors on nest survival has expanded greatly. We extend nest survival models further by introducing an approach to deal with incompletely observed, temporally varying covariates using a hierarchical model. Hierarchical modeling offers a way to separate process and observational components of demographic models to obtain estimates of the parameters of primary interest, and to evaluate structural effects of ecological and management interest. We built a hierarchical model for daily nest survival to analyze nest data from reintroduced whooping cranes (Grus americana) in the Eastern Migratory Population. This reintroduction effort has been beset by poor reproduction, apparently due primarily to nest abandonment by breeding birds. We used the model to assess support for the hypothesis that nest abandonment is caused by harassment from biting insects. We obtained indices of blood‐feeding insect populations based on the spatially interpolated counts of insects captured in carbon dioxide traps. However, insect trapping was not conducted daily, and so we had incomplete information on a temporally variable covariate of interest. We therefore supplemented our nest survival model with a parallel model for estimating the values of the missing insect covariates. We used Bayesian model selection to identify the best predictors of daily nest survival. Our results suggest that the black fly Simulium annulus may be negatively affecting nest survival of reintroduced whooping cranes, with decreasing nest survival as abundance of S. annulus increases. The modeling framework we have developed will be applied in the future to a larger data set to evaluate the biting‐insect hypothesis and other hypotheses for nesting failure in this reintroduced population; resulting inferences will support ongoing efforts to manage this population via an adaptive management approach. Wider application of our approach offers promise for modeling the effects of other temporally varying, but imperfectly observed covariates on nest survival, including the possibility of modeling temporally varying covariates collected from incubating adults.