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.     

Direct Quantification of the Attempt Frequency Determining the Mechanical Unfolding of Ubiquitin Protein

Understanding protein dynamics requires a comprehensive knowledge of the underlying potential energy surface that governs the motion of each individual protein molecule. Single molecule mechanical studies have provided the unprecedented opportunity to study the individual unfolding pathways along a well defined coordinate, the end-to-end length of the protein. In these experiments, unfolding requires surmounting an energy barrier that separates the native from the extended state. The calculation of the absolute value of the barrier height has traditionally relied on the assumption of an attempt frequency, υ^‡. Here we used single molecule force-clamp spectroscopy to directly determine the value of υ^‡ for mechanical unfolding by measuring the unfolding rate of the small protein ubiquitin at varying temperatures. Our experiments demonstrate a significant effect of the temperature on the mechanical rate of unfolding. By extrapolating the unfolding rate in the absence of force for different temperatures, varying within the range spanning from 5 to 45 °C, we measured a value for the activation barrier of ΔG^‡ = 71 ± 5 kJ/mol and an exponential prefactor υ^‡ ∼4 × 10⁹ s⁻¹. Although the measured prefactor value is 3 orders of magnitude smaller than the value predicted by the transition state theory (∼6 × 10¹² s⁻¹), it is 400-fold higher than that encountered in analogous experiments studying the effect of temperature on the reactivity of a protein-embedded disulfide bond (∼10⁷ m⁻¹ s⁻¹). This approach will allow quantitative characterization of the complete energy landscape of a folding polypeptide from highly extended states, of capital importance for proteins with elastic function.     

Small Molecule-facilitated Degradation of ANO1 Protein: A NEW TARGETING APPROACH FOR ANTICANCER THERAPEUTICS

ANO1, a calcium-activated chloride channel, is highly expressed and amplified in human cancers and is a critical survival factor in these cancers. The ANO1 inhibitor CaCC_inh-A01 decreases proliferation of ANO1-amplified cell lines; however, the mechanism of action remains elusive. We explored the mechanism behind the inhibitory effect of CaCC_inh-A01 on cell proliferation using a combined experimental and in silico approach. We show that inhibition of ANO1 function is not sufficient to diminish proliferation of ANO1-dependent cancer cells. We report that CaCC_inh-A01 reduces ANO1 protein levels by facilitating endoplasmic reticulum-associated, proteasomal turnover of ANO1. Washout of CaCC_inh-A01 rescued ANO1 protein levels and resumed cell proliferation. Proliferation of newly derived CaCC_inh-A01-resistant cell pools was not affected by CaCC_inh-A01 as compared with the parental cells. Consistently, CaCC_inh-A01 failed to reduce ANO1 protein levels in these cells, whereas ANO1 currents were still inhibited by CaCC_inh-A01, indicating that CaCC_inh-A01 inhibits cell proliferation by reducing ANO1 protein levels. Furthermore, we employed in silico methods to elucidate novel biological functions of ANO1 inhibitors. Specifically, we derived a pharmacophore model to describe inhibitors capable of promoting ANO1 degradation and report new inhibitors of ANO1-dependent cell proliferation. In summary, our data demonstrate that inhibition of the channel activity of ANO1 is not sufficient to inhibit ANO1-dependent cell proliferation, indicating that the role of ANO1 in cancer only partially depends on its function as a channel. Our results provide an impetus for gaining a deeper understanding of ANO1 modulation in cells and introduce a new targeting approach for antitumor therapy in ANO1-amplified cancers.     

Deep Crustal Communities of the Juan de Fuca Ridge Are Governed by Mineralogy

Volcanic ocean crust contains a global chemosynthetic microbial ecosystem that impacts ocean productivity, seawater chemistry and geochemical cycling. We examined the mineralogical effect on community structure in the aquifer ecosystem by using a four-year in situ colonization experiment with igneous minerals and glasses in Integrated Ocean Drilling Program Hole 1301A on the Juan de Fuca Ridge. Microbial community analysis and scanning electron microscopy revealed that olivine phases and iron-bearing minerals bore communities that were distinct from iron-poor phases. Communities were dominated by Archaeoglobaceae, Clostridia, Thermosipho, Desulforudis and OP1 lineages. Our results suggest that mineralogy determines microbial composition in the subseafloor aquifer ecosystem.     

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.     

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.     

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.