Predicting community characteristics from habitat conditions: fluvial fish and hydraulics

1. One current approach to the prediction of community characteristics is to use models of key local-scale processes (e.g. niche dimensions) affecting individuals and to estimate the effects of these attributes over larger scales. We tested this approach, focusing on how the hydraulic habitat structures fluvial fish communities. 2. We used a recent statistical habitat model to predict fish community characteristics in eleven reaches in the Rhône river basin in France. Predictions were made ‘blindly’ since most reaches were not used to calibrate the model. The model reflects species preferences for local hydraulics. We made predictions of the fish community from the local hydraulic conditions found in the reaches under low flow conditions. The overall abundance and the relative abundance (both as indices) of fish species, specific size classes and species traits (i.e. reproductive, trophic, morphological and others) were predicted. We summarized our predictions of the relative abundance of species as two ‘community structure indices’ using Principal Component Analysis. 3. Our predictions from low-flow hydraulics were compared with long-term observations of fish communities. The relative abundance of species actually observed depended largely on zoogeographic factors within the Rhône basin which could not be predicted by the model. The model predicted 13% of the variance in the indices of relative abundance at the species level and 23% of this variance at the trait level for all zoogeographic regions combined. However, when focused on reaches within a geographic region, the model explained up to 47% of the same variance. Therefore, geographic regions act as ‘filters’ on the relative abundance of species, but hydraulics do affect fish communities within a given geographical context. 4. For the synthetic ‘community structure indices’, we obtained good predictions from hydraulics independently of the geographical context (variance explained up to 95%). These indices were linked to simple key hydraulic characteristics of river reaches (Froude and/or Reynolds number). The indices enabled interpretations of the links between hydraulics, geomorphology, discharge and community patterns. These links were consistent with existing knowledge of species and their traits. 5. In addition to the above validations, the habitat model partly explained the observed effects of impoundment on fish communities. 6. The present results show that stream hydraulics strongly impact fish community structure. Consequently, our findings confirm that community characteristics can be predicted using models of the local-scale habitat requirements of the species forming the community.     

High plant diversity of lowland rainforest vestiges in eastern Madagascar

Based on cartography, floristic inventory and vegetation analysis in the north and south of the Eastern Domain of Madagascar we identified three original tropical rainforest types which are among the world's most biodiverse known sites for plants: the littoral forest on sand, the lowland forest on gneiss and the lowland forest on basalt. Floristic and structural comparisons were conducted on 37 plots of 50×10m. Multivariate analysis indicates that floristic composition is correlated with abiotic factors of rainfall, latitude, soil composition, and marine influence; the structure of the undergrowth is generally homogeneous and the canopy is more or less open. Many reserves must be created on gneiss, sand and basalt all along the eastern coast to preserve biodiversity from the deforestation process. On basalt, this is especially urgent because about only 10 000 ha of a very ancient forest that shelters numerous botanical novelties remain today.     

Endangered stands of thuriferous juniper in the western Mediterranean basin: ecological status, conservation and management

Thuriferous juniper is only found in isolated parts of the western Mediterranean: France (Alps, Pyrenees and Corsican highlands), Spain, Algeria and Morocco. These semi-arid mountain stands, where thuriferous juniper trees grow in low-density open woodland, are seriously endangered: (i) In the Atlas mountains, the thuriferous juniper stands are heavily degraded as a result of the intensive wood removal and livestock activity in these densely populated areas. This situation, which will soon become irreversible unless remedial measures are urgently taken, has produced impoverished soils and hillside instability while contributing to desertification. (ii) In Spain, although livestock activity and cultivation have strongly reduced areas occupied by Juniperus thurifera, stands are still numerous and, in some regions, show a good regeneration due to conservation measures. (iii) In France, the decline in human and livestock activities over recent decades has led to a recolonization of some of the Juniper stands by pines or oak. A forest management system that enables these original stands to survive and regenerate must be undertaken without delay. The dynamics of evolution of these stands is quite different north and south of the Mediterranean. In both cases, conservation measures are urgently required to protect or rehabilitate these original stands with floristic, ecological and socio-economic interest.     

High-performance liquid chromatographic determination of paclitaxel in rat serum: application to a toxicokinetic study

A simple and sensitive high-performance liquid chromatographic method is described for the determination of paclitaxel (Taxol^®) at 230 nm using a Nucleosil C₁₈ (5 μm) column and a methanol–water (70:30, v/v) mobile phase following a single-step extraction from serum with dichloromethane. The assay was validated against the classical criteria and was applied to a toxicokinetic study in rats after one or five, one per week) intraperitoneal administrations of 16 mg/kg Taxol^®.     

A field guide to cultivating computational biology

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions.

Biology in the digital era requires computation and collaboration. A modern research project may include multiple model systems, use multiple assay technologies, collect varying data types, and require complex computational strategies, which together make effective design and execution difficult or impossible for any individual scientist. While some labs, institutions, funding bodies, publishers, and other educators have already embraced a team science model in computational biology and thrived [1–7], others who have not yet fully adopted it risk severely lagging behind the cutting edge. We propose a general solution: “deep integration” between biology and the computational sciences. Many different collaborative models can yield deep integration, and different problems require different approaches (Fig 1).Open in a separate windowFig 1Supporting interdisciplinary team science will accelerate biological discoveries.Scientists who have little exposure to different fields build silos, in which they perform science without external input. To solve hard problems and to extend your impact, collaborate with diverse scientists, communicate effectively, recognize the importance of core facilities, and embrace research parasitism. In biologically focused parasitism, wet lab biologists use existing computational tools to solve problems; in computationally focused parasitism, primarily dry lab biologists analyze publicly available data. Both strategies maximize the use and societal benefit of scientific data.In this article, we define computational science extremely broadly to include all quantitative approaches such as computer science, statistics, machine learning, and mathematics. We also define biology broadly, including any scientific inquiry pertaining to life and its many complications. A harmonious deep integration between biology and computer science requires action—we outline 10 immediate calls to action in this article and aim our speech directly at individual scientists, institutions, funding agencies, and publishers in an attempt to shift perspectives and enable action toward accepting and embracing computational biology as a mature, necessary, and inevitable discipline (Box 1).Box 1. Ten calls to action for individual scientists, funding bodies, publishers, and institutions to cultivate computational biology. Many actions require increased funding support, while others require a perspective shift. For those actions that require funding, we believe convincing the community of need is the first step toward agencies and systems allocating sufficient support

1. Respect collaborators’ specific research interests and motivationsProblem: Researchers face conflicts when their goals do not align with collaborators. For example, projects with routine analyses provide little benefit for computational biologists.Solution: Explicit discussion about interests/expertise/goals at project onset.Opportunity: Clearly defined expectations identify gaps, provide commitment to mutual benefit.
2. Seek necessary input during project design and throughout the project life cycleProblem: Modern research projects require multiple experts spanning the project’s complexity.Solution: Engage complementary scientists with necessary expertise throughout the entire project life cycle.Opportunity: Better designed and controlled studies with higher likelihood for success.
3. Provide and preserve budgets for computational biologists’ workProblem: The perception that analysis is “free” leads to collaborator budget cuts.Solution: When budget cuts are necessary, ensure that they are spread evenly.Opportunity: More accurate, reproducible, and trustworthy computational analyses.
4. Downplay publication author order as an evaluation metric for computational biologistsProblem: Computational biologist roles on publications are poorly understood and undervalued.Solution: Journals provide more equitable opportunities, funding bodies and institutions improve understanding of the importance of team science, scientists educate each other.Opportunity: Engage more computational biologist collaborators, provide opportunities for more high-impact work.
5. Value software as an academic productProblem: Software is relatively undervalued and can end up poorly maintained and supported, wasting the time put into its creation.Solution: Scientists cite software, and funding bodies provide more software funding opportunities.Opportunity: More high-quality maintainable biology software will save time, reduce reimplementation, and increase analysis reproducibility.
6. Establish academic structures and review panels that specifically reward team scienceProblem: Current mechanisms do not consistently reward multidisciplinary work.Solution: Separate evaluation structures to better align peer review to reward indicators of team science.Opportunity: More collaboration to attack complex multidisciplinary problems.
7. Develop and reward cross-disciplinary training and mentoringProblem: Academic labs and institutions are often insufficiently equipped to provide training to tackle the next generation of biological problems, which require computational skills.Solution: Create better training programs aligned to necessary on-the-job skills with an emphasis on communication, encourage wet/dry co-mentorship, and engage younger students to pursue computational biology.Opportunity: Interdisciplinary students uncover important insights in their own data.
8. Support computing and experimental infrastructure to empower computational biologistsProblem: Individual computational labs often fund suboptimal cluster computing systems and lack access to data generation facilities.Solution: Institutions can support centralized compute and engage core facilities to provide data services.Opportunity: Time and cost savings for often overlooked administrative tasks.
9. Provide incentives and mechanisms to share open data to empower discovery through reanalysisProblem: Data are often siloed and have untapped potential.Solution: Provide institutional data storage with standardized identifiers and provide separate funding mechanisms and publishing venues for data reuse.Opportunity: Foster new breed of researchers, “research parasites,” who will integrate multimodal data and enhance mechanistic insights.
10. Consider infrastructural, ethical, and cultural barriers to clinical data accessProblem: Identifiable health data, which include sensitive information that must be kept hidden, are distributed and disorganized, and thus underutilized.Solution: Leadership must enforce policies to share deidentifiable data with interoperable metadata identifiers.Opportunity: Derive new insights from multimodal data integration and build datasets with increased power to make biological discoveries.

     

Kinetic Behavior of Some Polyphosphate-Accumulating Bacteria Isolates in the Presence of Nitrate and Oxygen

This paper studies the phosphate uptake by pure cultures of Aeromonas hydrophila, Klebsiella oxytoca, Agrobacterium tumefaciens, and Aquaspirillum dispar in the presence of both nitrate and oxygen. It is shown that species were able to respire both electron acceptors for phosphate accumulation. A. tumefaciens and A. dispar accumulated overall phosphate both in oxic and anoxic culture conditions, whereas A. hydrophila and K. oxytoca eliminated overall phosphate only in oxic conditions. A. dispar was able to remove phosphate by reducing oxygen and nitrate simultaneously with the production of dinitrogen gas. The anoxic denitrification observed in the cultures of adapted and nonadapted cells to nitrate showed that only A. dispar have a denitrification rate superior when the cells were adapted to nitrate. Received: 15 December 1998 / Accepted: 21 January 1999     

The CRL4DCAF1 cullin‐RING ubiquitin ligase is activated following a switch in oligomerization state

The cullin‐4‐based RING‐type (CRL4) family of E3 ubiquitin ligases functions together with dedicated substrate receptors. Out of the ˜29 CRL4 substrate receptors reported, the DDB1‐ and CUL4‐associated factor 1 (DCAF1) is essential for cellular survival and growth, and its deregulation has been implicated in tumorigenesis. We carried out biochemical and structural studies to examine the structure and mechanism of the CRL4^DCAF1 ligase. In the 8.4 Å cryo‐EM map of CRL4^DCAF1, four CUL4‐RBX1‐DDB1‐DCAF1 protomers are organized into two dimeric sub‐assemblies. In this arrangement, the WD40 domain of DCAF1 mediates binding with the cullin C‐terminal domain (CTD) and the RBX1 subunit of a neighboring CRL4^DCAF1 protomer. This renders RBX1, the catalytic subunit of the ligase, inaccessible to the E2 ubiquitin‐conjugating enzymes. Upon CRL4^DCAF1 activation by neddylation, the interaction between the cullin CTD and the neighboring DCAF1 protomer is broken, and the complex assumes an active dimeric conformation. Accordingly, a tetramerization‐deficient CRL4^DCAF1 mutant has higher ubiquitin ligase activity compared to the wild‐type. This study identifies a novel mechanism by which unneddylated and substrate‐free CUL4 ligases can be maintained in an inactive state.     

Xenopus Pax-6 and retinal development

We have cloned a homolog of Pax-6 in Xenopus laevis. Its deduced amino acid sequence has a 95% overall identity with Pax-6 homologs in other vertebrates. It is expressed early in development in cells fated to form the eye and parts of the forebrain, hindbrain, and spinal cord. It has two phases of expression in the eye. In the early phase, from stage 12.5 to stage 33/34, Xenopus Pax-6 is expressed throughout the developing retina. In the late phase, after stage 33/34, it is excluded from mature cells in the outer half of the retina and from cells in the ciliary marginal zone, remaining only in amacrine and ganglion cells. Misexpression of Pax-6 early in development results in axial defects, but no specific eye phenotype is observed. Targeted misexpression in the retina at later stages does not result in any significant bias toward formation of amacrine or ganglion cells or away from photoreceptors. Ectopic expression of the proneural gene NeuroD alters the pattern of Pax-6, substantially reducing its expression in the eye field and later reducing or eliminating the eye itself. Our results show that Pax-6 expression appears to be necessary, but not sufficient, for eye formation in Xenopus. © 1997 John Wiley & Sons, Inc. J Neurobiol 32, 45–61, 1997.