Using Small-Scale Studies to Prioritize Threats and Guide Recovery of a Rare Hemiparasitic Plant: Cordylanthus rigidus ssp. littoralis

Background

Recovering endangered species would benefit from identifying and ranking of the factors that threaten them. Simply managing for multiple positive influences will often aid in recovery; however, the relative impacts of multiple threats and/or interactions among them are not always predictable. We used a series of experiments and quantitative observational studies to examine the importance of five potential limiting factors to the abundance of a state-listed endangered hemiparasitic annual forb, Cordylanthus rigidus ssp. littoralis (C.r.l., California, USA): host availability, mammalian herbivores, insect seed predators, fire suppression, and exotic species. While this initial assessment is certainly not a complete list, these factors stem from direct observation and can inform provisional recommendations for management and further research.

Methodology and Principal Findings

Studies were conducted at five sites and included assessments of the influence of host availability, exotic species, exclusion of mammalian herbivores and insect seed predators on C.r.l. productivity, and simulated effects of fire on seed germination. C.r.l. was limited by multiple threats: individuals with access to host species produced up to three times more inflorescences than those lacking hosts, mammalian herbivory reduced C.r.l. size and fecundity by more than 50% and moth larvae reduced seed production by up to 40%. Litter deposition and competition from exotic plant species also appears to work in conjunction with other factors to limit C.r.l. throughout its life cycle.

Conclusions and Significance

The work reported here highlights the contribution that a series of small-scale studies can make to conservation and restoration. Taken as a whole, the results can be used immediately to inform current management and species recovery strategies. Recovery of C.r.l. will require management that addresses competition with exotic plant species, herbivore pressure, and availability of preferred host species.     

The Genome Sequence of Trypanosoma brucei gambiense,Causative Agent of Chronic Human African Trypanosomiasis

Background

Trypanosoma brucei gambiense is the causative agent of chronic Human African Trypanosomiasis or sleeping sickness, a disease endemic across often poor and rural areas of Western and Central Africa. We have previously published the genome sequence of a T. b. brucei isolate, and have now employed a comparative genomics approach to understand the scale of genomic variation between T. b. gambiense and the reference genome. We sought to identify features that were uniquely associated with T. b. gambiense and its ability to infect humans.

Methods and Findings

An improved high-quality draft genome sequence for the group 1 T. b. gambiense DAL 972 isolate was produced using a whole-genome shotgun strategy. Comparison with T. b. brucei showed that sequence identity averages 99.2% in coding regions, and gene order is largely collinear. However, variation associated with segmental duplications and tandem gene arrays suggests some reduction of functional repertoire in T. b. gambiense DAL 972. A comparison of the variant surface glycoproteins (VSG) in T. b. brucei with all T. b. gambiense sequence reads showed that the essential structural repertoire of VSG domains is conserved across T. brucei.

Conclusions

This study provides the first estimate of intraspecific genomic variation within T. brucei, and so has important consequences for future population genomics studies. We have shown that the T. b. gambiense genome corresponds closely with the reference, which should therefore be an effective scaffold for any T. brucei genome sequence data. As VSG repertoire is also well conserved, it may be feasible to describe the total diversity of variant antigens. While we describe several as yet uncharacterized gene families with predicted cell surface roles that were expanded in number in T. b. brucei, no T. b. gambiense-specific gene was identified outside of the subtelomeres that could explain the ability to infect humans.     

Honeybee Associative Learning Performance and Metabolic Stress Resilience Are Positively Associated

Background

Social-environmental influences can affect animal cognition and health. Also, human socio-economic status is a covariate factor connecting psychometric test-performance (a measure of cognitive ability), educational achievement, lifetime health, and survival. The complimentary hypothesis, that mechanisms in physiology can explain some covariance between the same traits, is disputed. Possible mechanisms involve metabolic biology affecting integrity and stability of physiological systems during development and ageing. Knowledge of these relationships is incomplete, and underlying processes are challenging to reveal in people. Model animals, however, can provide insights into connections between metabolic biology and physiological stability that may aid efforts to reduce human health and longevity disparities.

Results

We document a positive correlation between a measure of associative learning performance and the metabolic stress resilience of honeybees. This relationship is independent of social factors, and may provide basic insights into how central nervous system (CNS) function and metabolic biology can be associated. Controlling for social environment, age, and learning motivation in each bee, we establish that learning in Pavlovian conditioning to an odour is positively correlated with individual survival time in hyperoxia. Hyperoxia induces oxidative metabolic damage, and provides a measure of metabolic stress resistance that is often related to overall lifespan in laboratory animals. The positive relationship between Pavlovian learning ability and stress resilience in the bee is not equally established in other model organisms so far, and contrasts with a genetic cost of improved associative learning found in Drosophila melanogaster.

Conclusions

Similarities in the performances of different animals need not reflect common functional principles. A correlation of honeybee Pavlovian learning and metabolic stress resilience, thereby, is not evidence of a shared biology that will give insight about systems integrity in people. Yet, the means to resolve difficult research questions often come from findings in distant areas of science while the model systems that turn out to be valuable are sometimes the least predictable. Our results add to recent findings indicating that honeybees can become instrumental to understanding how metabolic biology influences life outcomes.     

The initial step in human immunodeficiency virus type 1 GagProPol processing can be regulated by reversible oxidation

Background

Maturation of human immunodeficiency virus type 1 (HIV-1) occurs upon activation of HIV-1 protease embedded within GagProPol precursors and cleavage of Gag and GagProPol polyproteins. Although reversible oxidation can regulate mature protease activity as well as retrovirus maturation, it is possible that the effects of oxidation on viral maturation are mediated in whole, or part, through effects on the initial intramolecular cleavage event of GagProPol. In order assess the effect of reversible oxidation on this event, we developed a system to isolate the first step in protease activation involving GagProPol.

Methodology/Principal Findings

To determine if oxidation influences this step, we created a GagProPol plasmid construct (pGPfs-1C) that encoded mutations at all cleavage sites except p2/NC, the initial cleavage site in GagProPol. pGPfs-1C was used in an in vitro translation assay to observe the behavior of this initial step without interference from subsequent processing events. Diamide, a sulfhydral oxidizing agent, inhibited processing at p2/NC by >60% for pGPfs-1C and was readily reversed with the reductant, dithiothreitol. The ability to regulate processing by reversible oxidation was lost when the cysteines of the embedded protease were mutated to alanine. Unlike mature protease, which requires only oxidation of cys95 for inhibition, both cysteines of the embedded protease contributed to this inhibition.

Conclusions/Significance

We developed a system that can be used to study the first step in the cascade of HIV-1 GagProPol processing and show that reversible oxidation of cysteines of HIV-1 protease embedded in GagProPol can block this initial GagProPol autoprocessing. This type of regulation may be broadly applied to the majority of retroviruses.     

The Effect of Map Boundary on Estimates of Landscape Resistance to Animal Movement

Background

Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat.

Methodology/Principal Findings

We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance.

Conclusions/Significance

Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies.     

Dealing with detection error in site occupancy surveys: what can we do with a single survey?

Aim Site occupancy probabilities of target species are commonly used in various ecological studies, e.g. to monitor current status and trends in biodiversity. Detection error introduces bias in the estimators of site occupancy. Existing methods for estimating occupancy probability in the presence of detection error use replicate surveys. These methods assume population closure, i.e. the site occupancy status remains constant across surveys, and independence between surveys. We present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or independence. In place of the closure assumption, this method requires covariates that affect detection and occupancy.Methods Penalized maximum-likelihood method was used to estimate the parameters. Estimability of the parameters was checked using data cloning. Parametric boostrapping method was used for computing confidence intervals.Important findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable, situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not met. This method saves significant amounts of time, energy and money in ecological surveys without sacrificing statistical validity. Further, we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.     

Measuring succession: methods for establishing long-term vegetation monitoring sites

Successional stages are often characterized by dominant plant species (species with the highest cover) and their effect on the structure and function of an area through time. However, the plant species determining the ecosystem properties and plant community dynamics may not be the dominant, especially when it is exotic. Understanding plant community dynamics in ecosystems that are uncharacterized and/or affected by invasive plant species requires a data-driven approach and proper placement of monitoring plots. To generate robust datasets on vegetation change through time, monitoring plot placement must consider the scale of ecological variation for both vegetation and soils and plots would ideally be replicated within similar ecological site types to quantify the consistency of successional transitions. We characterized soil and vegetation across and within seven floodplains affected by Russian olive (Elaeagnus angustifolia L.) along the Yellowstone River in southeastern Montana, USA. Using modern Classification and Regression Trees (CART) and multivariate net differentiation, we identified five distinct plant community types, or classes, characterized by their tertiary woody plant cover, not the primary species, Russian olive. Our findings indicate that Russian olive communities differ across space, and these riparian areas can be classified into distinct plant community types. Characterizing plant community types via this analytical approach should allow practitioners to modify management decisions and forecast succession within relevant plant communities.