FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Cyclic Expression of A Nuclear Protein In A Dinoflagellate

Nuclei of the dinoflagellate Crypthecodinium cohnii strain Whd were isolated and nuclear proteins were extracted in three fractions, corresponding to the increasing affinity of these proteins to genomic DNA. One fraction contained two major bands (48- and 46-kDa) and antibodies specific to this fraction revealed two major bands by Western blot on nuclear extracts, corresponding to the 46- and 48-kDa bands. The 48-kDa protein was detected in G1 phase but not in M phase cells. An expression cDNA library of C. cohnii was screened with these antibodies, and two different open reading frames were isolated. Dinoflagellate nuclear associated protein (Dinap1), one of these coding sequences, was produced in E. coli and appeared to correspond to the 48-kDa nuclear protein. No homologue of this sequence was found in the data bases, but two regions were identified, one including two putative zinc finger repeats, and one coding for two potential W/W domains. The second coding sequence showed a low similarity to non-specific sterol carrier proteins. Immunocytolocalization with specific polyclonal antibodies to recombinant Dinap1 showed that the nucleus was immunoreactive only during the G1 phase: the nucleoplasm was immunostained, while chromosome cores and nuclear envelopes were negative.     

Large-scale identification of polymorphic microsatellites using an <Emphasis Type="Italic">in silico</Emphasis> approach

Background  

Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last decade, although testing putative SSR markers still is time consuming and expensive. In many species only a relatively small percentage of SSR markers turn out to be polymorphic. This is particularly true for markers derived from expressed sequence tags (ESTs). In EST databases a large redundancy of sequences is present, which may contain information on length-polymorphisms in the SSR they contain, and whether they have been derived from heterozygotes or from different genotypes. Up to now, although a number of programs have been developed to identify SSRs in EST sequences, no software can detect putatively polymorphic SSRs.     

Ecologically heterogeneous populations of the invasive ant Wasmannia auropunctata within its native and introduced ranges

Abstract 1. The biology of most invasive species in their native geographical areas remains largely unknown. Such studies are, however, crucial in shedding light on the ecological and evolutionary processes underlying biological invasions. 2. The present study focuses on the little fire ant Wasmannia auropunctata, a species native to Central and South America that has been widely introduced and which has become invasive throughout the tropics. We characterise and compare several ecological traits of native populations in French Guiana with those in one of its introduced ranges, New Caledonia. 3. We found ecologically heterogeneous populations of W. auropunctata coexisting in the species’ native geographical area. First, we found populations restricted to naturally perturbed areas (particularly floodplains) within the primary forest, and absent from the surrounding forest areas. These populations were characterised by low nest and worker densities. Second, we found dominant populations in recent anthropogenic areas (e.g. secondary forest or forest edge along road) characterised by high nest and worker densities, and associated with low ant species richness. The local dominance of W. auropunctata in such areas can be due to the displacement of other species (cause) or the filling‐up of empty habitats unsuitable to other ants (effect). With respect to their demographic features and ant species richness, the populations of native anthropogenic habitats were to a large extent similar to the invasive populations introduced into remote areas. 4. The results point to the need for greater research efforts to better understand the ecological and demographic features of invasive species within their native ranges.     

Carbon accumulation in agricultural soils after afforestation: a meta-analysis

Deforestation usually results in significant losses of soil organic carbon (SOC). The rate and factors determining the recovery of this C pool with afforestation are still poorly understood. This paper provides a review of the influence of afforestation on SOC stocks based on a meta-analysis of 33 recent publications (totaling 120 sites and 189 observations), with the aim of determining the factors responsible for the restoration of SOC following afforestation. Based on a mixed linear model, the meta-analysis indicates that the main factors that contribute to restoring SOC stocks after afforestation are: previous land use, tree species planted, soil clay content, preplanting disturbance and, to a lesser extent, climatic zone. Specifically, this meta-analysis (1) indicates that the positive impact of afforestation on SOC stocks is more pronounced in cropland soils than in pastures or natural grasslands; (2) suggests that broadleaf tree species have a greater capacity to accumulate SOC than coniferous species; (3) underscores that afforestation using pine species does not result in a net loss of the whole soil-profile carbon stocks compared with initial values (agricultural soil) when the surface organic layer is included in the accounting; (4) demonstrates that clay-rich soils (> 33%) have a greater capacity to accumulate SOC than soils with a lower clay content (< 33%); (5) indicates that minimizing preplanting disturbances may increase the rate at which SOC stocks are replenished; and (6) suggests that afforestation carried out in the boreal climate zone results in small SOC losses compared with other climate zones, probably because trees grow more slowly under these conditions, although this does not rule out gains over time after the conversion. This study also highlights the importance of the methodological approach used when developing the sampling design, especially the inclusion of the organic layer in the accounting.     

The Effect of Bumpy Structure on Optical Properties of Bimetallic Nanoshells

In this paper, a sensitive bumpy bimetallic nanoshell for detection of thyroid cancer market (Thyroglobulin, Tg) and bovine serum albumin (BSA) proteins is reported. The physical origin of plasmonic properties of bimetal nanoshells is described by plasmon hybridization theory which indicates three intense and clearly separated plasmon modes. The electric field intensity enhancement of the bumpy bimetal nanoshell increases by ~559 %, at the surface of the bump in comparison with a smooth shell. The presence of bumpy structure on the nanoshell surface provides a high enhancement of the resulting Raman signal through an electromagnetic field of the order of 10⁷ which leads to an increase in sensitivity detection of Tg and BSA proteins. In addition, a refractive index (RI) sensitivity of 332.54 nm/RIU is achieved for this bumpy bimetallic nanoshell.     

Bootstrapping phylogenies inferred from rearrangement data

ABSTRACT: Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver-operating characteristics are nearly identical, indicating that it provides similar levels of sensitivity and specificity. Thus our assessment method makes it possible to conduct phylogenetic analyses on whole genomes with the same degree of confidence as for analyses on aligned sequences. Extensions to search-based inference methods such as maximum parsimony and maximum likelihood are possible, but remain to be thoroughly tested.     

Novel and Sensitive Core-Shell Nanoparticles Based on Surface Plasmon Resonance

In this paper, a rough silver core-shell nanoparticle with strong electric field enhancement in the vicinity of a bumpy structure on the silver core-shell surface is reported. A dipolar plasmonic mode of the silver nanoshell is investigated by using the quasi-static approach and plasmon hybridization theory, which analytical results identify the electric field enhancement spectra in which the enhancement is optimized. As the silver shell thickness is small, the hot spots play an important role in the plasmonic field enhancement. In addition, the deposition of a rough silver shell can generate a stronger near-field enhancement near the silver surface which is more desirable than that of a smooth silver shell for sensitive detection based on SPR and surface enhanced Raman scattering (SERS). The plasmonic field enhancement of a bumpy silver core-shell nanoparticle permits the detection and characterization of bovine serum albumin (BSA) protein molecule and hemoglobin solution with a high sensitivity.