The potential natural vegetation of large river floodplains - from dynamic to static equilibrium

Article in PressThe potential natural vegetation (PNV) is a useful benchmark for the restoration of large river floodplains because very few natural reference reaches exist. Expert-based approaches and different types of ecological models (static and dynamic) are commonly used for its estimation despite the conceptual differences they imply. For natural floodplains a static concept of PNV is not reasonable, as natural disturbances cause a constant resetting of succession. However, various forms of river regulation have disrupted the natural dynamics of most large European rivers for centuries. Therefore, we asked whether the consideration of succession dynamics and time dependent habitat turnover are still relevant factors for the reconstruction of the PNV. To answer this we compared the results of a simulation of the vegetation succession (1872–2016) of a segment of the upper Rhine river after regulation (damming, straightening and bank protection) to different statistic and expert-based modelling approaches for PNV reconstruction. The validation of the different PNV estimation methods against a set of independent reference plots and the direct comparison of their results revealed very similar performances. We therefore conclude that due to a lack of large disturbances, the vegetation of regulated large rivers has reached a near-equilibrium state with the altered hydrologic regime and that a static perception of its PNV may be justified. Consequently, statistical models seem to be the best option for its reconstruction since they need relatively few resources (data, time, expert knowledge) and are reproducibleinfo:eu-repo/semantics/acceptedVersio

Stability and Complexity of Minimising Probabilistic Automata

We consider the state-minimisation problem for weighted and probabilistic automata. We provide a numerically stable polynomial-time minimisation algorithm for weighted automata, with guaranteed bounds on the numerical error when run with floating-point arithmetic. Our algorithm can also be used for "lossy" minimisation with bounded error. We show an application in image compression. In the second part of the paper we study the complexity of the minimisation problem for probabilistic automata. We prove that the problem is NP-hard and in PSPACE, improving a recent EXPTIME-result.Comment: This is the full version of an ICALP'14 pape

Array algorithms for H^2 and H^∞ estimation

Currently, the preferred method for implementing H^2 estimation algorithms is what is called the array form, and includes two main families: square-root array algorithms, that are typically more stable than conventional ones, and fast array algorithms, which, when the system is time-invariant, typically offer an order of magnitude reduction in the computational effort. Using our recent observation that H^∞ filtering coincides with Kalman filtering in Krein space, in this chapter we develop array algorithms for H^∞ filtering. These can be regarded as natural generalizations of their H^2 counterparts, and involve propagating the indefinite square roots of the quantities of interest. The H^∞ square-root and fast array algorithms both have the interesting feature that one does not need to explicitly check for the positivity conditions required for the existence of H^∞ filters. These conditions are built into the algorithms themselves so that an H^∞ estimator of the desired level exists if, and only if, the algorithms can be executed. However, since H^∞ square-root algorithms predominantly use J-unitary transformations, rather than the unitary transformations required in the H^2 case, further investigation is needed to determine the numerical behavior of such algorithms

A mathematical framework for contact detection between quadric and superquadric surfaces

The calculation of the minimum distance between surfaces plays an important role in computational mechanics, namely, in the study of constrained multibody systems where contact forces take part. In this paper, a general rigid contact detection methodology for non-conformal bodies, described by ellipsoidal and superellipsoidal surfaces, is presented. The mathematical framework relies on simple algebraic and differential geometry, vector calculus, and on the C2 continuous implicit representations of the surfaces. The proposed methodology establishes a set of collinear and orthogonal constraints between vectors defining the contacting surfaces that, allied with loci constraints, which are specific to the type of surface being used, formulate the contact problem. This set of non-linear equations is solved numerically with the Newton-Raphson method with Jacobian matrices calculated analytically. The method outputs the coordinates of the pair of points with common normal vector directions and, consequently, the minimum distance between both surfaces. Contrary to other contact detection methodologies, the proposed mathematical framework does not rely on polygonal-based geometries neither on complex non-linear optimization formulations. Furthermore, the methodology is extendable to other surfaces that are (strictly) convex, interact in a non-conformal fashion, present an implicit representation, and that are at least C2 continuous. Two distinct methods for calculating the tangent and binormal vectors to the implicit surfaces are introduced: (i) a method based on the Householder reflection matrix; and (ii) a method based on a square plate rotation mechanism. The first provides a base of three orthogonal vectors, in which one of them is collinear to the surface normal. For the latter, it is shown that, by means of an analogy to the referred mechanism, at least two non-collinear vectors to the normal vector can be determined. Complementarily, several mathematical and computational aspects, regarding the rigid contact detection methodology, are described. The proposed methodology is applied to several case tests involving the contact between different (super)ellipsoidal contact pairs. Numerical results show that the implemented methodology is highly efficient and accurate for ellipsoids and superellipsoids.Fundação para a Ciência e a Tecnologia (FCT

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification

<p>Abstract</p> <p>Background</p> <p>Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods.</p> <p>Results</p> <p>Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (<b>SVD</b>-based <b>P</b>attern <b>P</b>airing and <b>C</b>hart <b>S</b>plitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W¹¹⁸of <it>M. drosophila</it>. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering.</p> <p>Conclusions</p> <p>svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.</p

Low-Spin Heme b3 in the Catalytic Center of Nitric Oxide Reductase from Pseudomonas nautica

Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605pRespiratory nitric oxide reductase (NOR) was purified from membrane extract of Pseudomonas (Ps.) nautica cells to homogeneity as judged by polyacrylamide gel electrophoresis. The purified protein is a heterodimer with subunits of molecular masses of 54 and 18 kDa. The gene encoding both subunits was cloned and sequenced. The amino acid sequence shows strong homology with enzymes of the cNOR class. Iron/heme determinations show that one heme c is present in the small subunit (NORC) and that approximately two heme b and one non-heme iron are associated with the large subunit (NORB), in agreement with the available data for enzymes of the cNOR class. Mössbauer characterization of the as-purified, ascorbate-reduced, and dithionite-reduced enzyme confirms the presence of three heme groups (the catalytic heme b(3) and the electron transfer heme b and heme c) and one redox-active non-heme Fe (Fe(B)). Consistent with results obtained for other cNORs, heme c and heme b in Ps. nautica cNOR were found to be low-spin while Fe(B) was found to be high-spin. Unexpectedly, as opposed to the presumed high-spin state for heme b(3), the Mössbauer data demonstrate unambiguously that heme b(3) is, in fact, low-spin in both ferric and ferrous states, suggesting that heme b(3) is six-coordinated regardless of its oxidation state. EPR spectroscopic measurements of the as-purified enzyme show resonances at the g ∼ 6 and g ∼ 2-3 regions very similar to those reported previously for other cNORs. The signals at g = 3.60, 2.99, 2.26, and 1.43 are attributed to the two charge-transfer low-spin ferric heme c and heme b. Previously, resonances at the g ∼ 6 region were assigned to a small quantity of uncoupled high-spin Fe(III) heme b(3). This assignment is now questionable because heme b(3) is low-spin. On the basis of our spectroscopic data, we argue that the g = 6.34 signal is likely arising from a spin-spin coupled binuclear center comprising the low-spin Fe(III) heme b(3) and the high-spin Fe(B)(III). Activity assays performed under various reducing conditions indicate that heme b(3) has to be reduced for the enzyme to be active. But, from an energetic point of view, the formation of a ferrous heme-NO as an initial reaction intermediate for NO reduction is disfavored because heme [FeNO](7) is a stable product. We suspect that the presence of a sixth ligand in the Fe(II)-heme b(3) may weaken its affinity for NO and thus promotes, in the first catalytic step, binding of NO at the Fe(B)(II) site. The function of heme b(3) would then be to orient the Fe(B)-bound NO molecules for the formation of the N-N bond and to provide reducing equivalents for NO reduction

Risks to carbon storage from land-use change revealed by peat thickness maps of Peru

This work was funded by NERC (grant ref. NE/R000751/1) to I.T.L., A.H., K.H.R., E.T.A.M., C.M.A., T.R.B., G.D. and E.C.D.G.; Leverhulme Trust (grant ref. RPG-2018-306) to K.H.R., L.E.S.C. and C.E.W.; Gordon and Betty Moore Foundation (grant no. 5439, MonANPeru network) to T.R.B., E.N.H.C. and G.F.; Wildlife Conservation Society to E.N.H.C.; Concytec/British Council/Embajada Británica Lima/Newton Fund (grant ref. 220–2018) to E.N.H.C. and J.D.; Concytec/NERC/Embajada Británica Lima/Newton Fund (grant ref. 001–2019) to E.N.H.C. and N.D.; the governments of the United States (grant no. MTO-069018) and Norway (grant agreement no. QZA-12/0882) to K.H.; and NERC Knowledge Exchange Fellowship (grant ref no. NE/V018760/1) to E.N.H.C.Tropical peatlands are among the most carbon-dense ecosystems but land-use change has led to the loss of large peatland areas, associated with substantial greenhouse gas emissions. To design effective conservation and restoration policies, maps of the location and carbon storage of tropical peatlands are vital. This is especially so in countries such as Peru where the distribution of its large, hydrologically intact peatlands is poorly known. Here field and remote sensing data support the model development of peatland extent and thickness for lowland Peruvian Amazonia. We estimate a peatland area of 62,714 km2 (5th and 95th confidence interval percentiles of 58,325 and 67,102 km2, respectively) and carbon stock of 5.4 (2.6–10.6) PgC, a value approaching the entire above-ground carbon stock of Peru but contained within just 5% of its land area. Combining the map of peatland extent with national land-cover data we reveal small but growing areas of deforestation and associated CO2 emissions from peat decomposition due to conversion to mining, urban areas and agriculture. The emissions from peatland areas classified as forest in 2000 represent 1–4% of Peruvian CO2 forest emissions between 2000 and 2016. We suggest that bespoke monitoring, protection and sustainable management of tropical peatlands are required to avoid further degradation and CO2 emissions.PostprintPeer reviewe

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km2) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km$^2$ (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin

Response of testate amoebae to a late Holocene ecosystem shift in an Amazonian peatland

To date there have only been two studies using testate amoebae as palaeoecological indicators in tropical peatlands. Here we present a new ∼500-year testate amoeba record from San Jorge, a domed peatland in Peruvian Amazonia, which has a well-constrained vegetation history based on pollen analysis. We observe a major shift from Hyalosphenia subflava to Cryptodifflugia oviformis-dominated communities at ∼50 cm depth (c. AD 1760), which suggests a change to drier conditions in the peatland. The application of a statistical transfer function also suggests a deepening of the water table at this time. The transition in the microbial assemblage occurs at a time when pollen and geochemical data indicate drier conditions (reduced influence of river flooding), leading to an ecosystem switch to more ombrotrophic-like conditions in the peatland. Our work illustrates the potential of testate amoebae as important tools in tropical peatland palaeoecology, and the power of multiproxy approaches for understanding the long-term development of tropical peatlands

Geography and ecology shape the phylogenetic composition of Amazonian tree communities.

Aim Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location Amazonia. Taxon Angiosperms (Magnoliids; Monocots; Eudicots). Methods Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results In the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion Numerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions.Na publicação: Joice Ferreira