The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Mid- to Late Holocene shoreline reconstruction and human occupation in Ancient Eretria (South Central Euboea, Greece)

Few studies have aimed to reconstruct landscape change in the area of Eretria (South Central Euboea, Greece) during the last 6000 years. The aim of this paper is to partially fill in this gap by examining the interaction be- tween Mid- to Late Holocene shoreline evolution and human occupation, which is documented in the area from the Late Neolithic to the Late Roman period (with discontinuities). Evidence of shoreline displacements is derived from the study of five boreholes (maximum depth of 5.25 m below the surface) drilled in the lowlands of Eretria. Based on sedimentological analyses and micro/macrofaunal identifications, different facies have been identified in the cores and which reveal typical features of deltaic progradation with marine, lagoonal, fluvio- deltaic and fluvial environments. In addition, a chronostratigraphy has been obtained based on 20 AMS 14C radio- carbon dates performed on samples of plant remains and marine/lagoonal shells found in situ. The main sequences of landscape reconstruction in the plain of Eretria can be summarized as follows: a marine environ- ment predominated from ca. 4000 to 3200 cal. BC and a gradual transition to shallow marine conditions is ob- served ca. 3200-3000 cal. BC due to the general context of deltaic progradation west of the ancient city. Subsequently, from ca. 3000 to 2000 cal. BC, a lagoon occupied the area in the vicinity of the Temple of Apollo and the settlement's development was restricted to several fluvio-deltaic levees, thus severely limiting human activities in the plain. From ca. 2000 to 800 cal. BC, a phase of shallow marine presence prevailed and constrained settlement on higher ground, forcing abandonment of the major part of the plain. Finally, since the eighth century BC, the sea has regressed southward and created the modern landscape.

Beyond the caves: the Palaeolithic rivers of south-west Britain

This paper introduces a new English Heritage (Aggregates Levy Sustainability Fund) project The Palaeolithic Rivers of South-West Britain (project no. 3847), and summarises the results of a first phase resource assessment. The goal of this ongoing project is to develop a new synthesis of the Lower and Middle Palaeolithic occupation of the south-west region, focusing upon river terrace-based archaeology and its implications for hominin landscape use. The resource assessment has reached two preliminary conclusions. Firstly that the region’s earliest Palaeolithic archaeological record is significantly richer than previously believed, and secondly that although find locations have been added in several areas which previously had very few or no finds (e.g.West Cornwall) the overall bias of finds to the south coast is maintained. The project has also revealed that the river terrace resource of South-West England offers potential for geochronological dating, landscape reconstruction, and improved contextualisation of the archaeological material. Some outreach components of the project are also summarised.

(Table 1) Radiocarbon and OSL ages of sediment cores C1-C5 drilled during the COAST expedition to Cape Mamontov Klyk in April 2005

The palaeoenvironmental development of the western Laptev Sea is understood primarily from investigations of exposed cliffs and surface sediment cores from the shelf. In 2005, a core transect was drilled between the Taymyr Peninsula and the Lena Delta, an area that was part of the westernmost region of the non-glaciated Beringian landmass during the late Quaternary. The transect of five cores, one terrestrial and four marine, taken near Cape Mamontov Klyk reached 12 km offshore and 77 m below sea level. A multiproxy approach combined cryolithological, sedimentological, geochronological (14C-AMS, OSL on quartz, IR-OSL on feldspars) and palaeoecological (pollen, diatoms) methods. Our interpretation of the proxies focuses on landscape history and the transition of terrestrial into subsea permafrost. Marine interglacial deposits overlain by relict terrestrial permafrost within the same offshore core were encountered in the western Laptev Sea. Moreover, the marine interglacial deposits lay unexpectedly deep at 64 m below modern sea level 12 km from the current coastline, while no marine deposits were encountered onshore. This implies that the position of the Eemian coastline presumably was similar to today's. The landscape reconstruction suggests Eemian coastal lagoons and thermokarst lakes, followed by Early to Middle Weichselian fluvially dominated terrestrial deposition. During the Late Weichselian, this fluvial landscape was transformed into a poorly drained accumulation plain, characterized by widespread and broad ice-wedge polygons. Finally, the shelf plain was flooded by the sea during the Holocene, resulting in the inundation and degradation of terrestrial permafrost and its transformation into subsea permafrost.

Optimal 3D surface reconstruction from multiview photographic images

This paper describes a new method for reconstructing 3D surface using a small number, e.g. 10, of 2D photographic images. The images are taken at different viewing directions by a perspective camera with full prior knowledge of the camera configurations. The reconstructed object's surface is represented a set of triangular facets. We empirically demonstrate that if the viewing directions are uniformly distributed around the object's viewing sphere, then the reconstructed 3D points optimally cluster closely on a highly curved part of the surface and are widely, spread on smooth or fat parts. The advantage of this property is that the reconstructed points along a surface or a contour generator are not undersampled or underrepresented because surfaces or contours should be sampled or represented with more densely points where their curvatures are high. The more complex the contour's shape, the greater is the number of points required, but the greater the number of points is automatically generated by the proposed method Given that the viewing directions are uniformly distributed, the number and distribution of the reconstructed points depend on the shape or the curvature of the surface regardless of the size of the surface or the size of the object.

Optimal 3D surface reconstruction from a small number of conventional 2D X-ray images

This paper describes a method for reconstructing 3D frontier points, contour generators and surfaces of anatomical objects or smooth surfaces from a small number, e. g. 10, of conventional 2D X-ray images. The X-ray images are taken at different viewing directions with full prior knowledge of the X-ray source and sensor configurations. Unlike previous works, we empirically demonstrate that if the viewing directions are uniformly distributed around the object's viewing sphere, then the reconstructed 3D points automatically cluster closely on a highly curved part of the surface and are widely spread on smooth or flat parts. The advantage of this property is that the reconstructed points along a surface or a contour generator are not under-sampled or under-represented because surfaces or contours should be sampled or represented with more densely points where their curvatures are high. The more complex the contour's shape, the greater is the number of points required, but the greater the number of points is automatically generated by the proposed method. Given that the number of viewing directions is fixed and the viewing directions are uniformly distributed, the number and distribution of the reconstructed points depend on the shape or the curvature of the surface regardless of the size of the surface or the size of the object. The technique may be used not only in medicine but also in industrial applications.

Biomarkers and inorganic proxies in the paleoenvironmental reconstruction of mires: The importance of landscape in Las Conchas (Asturias, Northern Spain)

We determined the lipid distributions (n-alkanes, n-alkan-2-ones, n-alkanoic acids), total organic carbon (TOC), total nitrogen (TN), Ca/Mg and ash content in Las Conchas mire, a 3.2 m deep bryophyte-dominated mire in Northern Spain covering 8000 cal yr BP. Bog conditions developed in the bottom 20 cm of the profile, and good preservation of organic matter (OM) was inferred from n-alkanoic acid distribution, with the exception of the uppermost 20 cm (last ca. 200 yr). Microbial synthesis of long chain saturated fatty acids from primary OM likely produced a dominance of short chain n-alkanoic acids with a bimodal distribution, as well as the lack of correspondence between the n-alkane and n-alkanoic acid profiles in the upper 20 cm. This was accompanied by an increase in ash content, a decrease in TOC and variation in n-alkane ratios, thereby suggesting significant changes in the mire, namely drainage and transformation to a meadow, in the last ca. 200 yr. The distribution of n-alkan-2-ones indicated an increase in bacterial source from the bottom of the record to 94 cm, whereas their distribution in the upper part could be attributed mainly to plant input and/or the microbial oxidation of n-alkanes. The different n-alkane proxies showed variations, which we interpreted in terms of changes in vegetation (Sphagnum vs. non-Sphagnum dominated phases) during the last 8000 cal yr BP. C23 was the most abundant homolog throughout most of the record, thereby suggesting dominant humid conditions alternating with short drier phases. However, such humid conditions were not linked to paleoclimatic variation but rather to geomorphological characteristics: Las Conchas mire, at the base of the Cuera Range, receives continuous runoff—even during drier periods—which is not necessarily accompanied by additional mineral input to peat, producing the development of Sphagnum moss typical of waterlogged ecotopes and damp habitats. Thus, although geochemical proxies indicated an ombrotrophic regime in the mire, geomorphological characteristics may make a considerable contribution to environmental conditions.

Local optimal scale in a hierarchical segmentation method for satellite image: an OBIA approach for the agricultural landscape

Overrecentdecades,remotesensinghasemergedasaneffectivetoolforimprov- ing agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hierarchically structured, the determination of optimal study scales is mandatory in understanding these processes and their interactions. The concept of multi-scale/multi- resolution inherent to OBIA methodologies allows the scale problem to be dealt with. But for that multi-scale and hierarchical segmentation algorithms are required. The question that remains unsolved is to determine the suitable scale segmentation that allows different objects and phenomena to be characterized in a single image. In this work, an adaptation of the Simple Linear Iterative Clustering (SLIC) algorithm to perform a multi-scale hierarchi- cal segmentation of satellite images is proposed. The selection of the optimal multi-scale segmentation for different regions of the image is carried out by evaluating the intra- variability and inter-heterogeneity of the regions obtained on each scale with respect to the parent-regions defined by the coarsest scale. To achieve this goal, an objective function, that combines weighted variance and the global Moran index, has been used. Two different kinds of experiment have been carried out, generating the number of regions on each scale through linear and dyadic approaches. This methodology has allowed, on the one hand, the detection of objects on different scales and, on the other hand, to represent them all in a sin- gle image. Altogether, the procedure provides the user with a better comprehension of the land cover, the objects on it and the phenomena occurring.

Low-dose multidetector computed tomography of the cervical spine: optimization of iterative reconstruction strength levels.

BACKGROUND: Iterative reconstruction (IR) techniques reduce image noise in multidetector computed tomography (MDCT) imaging. They can therefore be used to reduce radiation dose while maintaining diagnostic image quality nearly constant. However, CT manufacturers offer several strength levels of IR to choose from. PURPOSE: To determine the optimal strength level of IR in low-dose MDCT of the cervical spine. MATERIAL AND METHODS: Thirty consecutive patients investigated by low-dose cervical spine MDCT were prospectively studied. Raw data were reconstructed using filtered back-projection and sinogram-affirmed IR (SAFIRE, strength levels 1 to 5) techniques. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured at C3-C4 and C6-C7 levels. Two radiologists independently and blindly evaluated various anatomical structures (both dense and soft tissues) using a 4-point scale. They also rated the overall diagnostic image quality using a 10-point scale. RESULTS: As IR strength levels increased, image noise decreased linearly, while SNR and CNR both increased linearly at C3-C4 and C6-C7 levels (P < 0.001). For the intervertebral discs, the content of neural foramina and dural sac, and for the ligaments, subjective image quality scores increased linearly with increasing IR strength level (P ≤ 0.03). Conversely, for the soft tissues and trabecular bone, the scores decreased linearly with increasing IR strength level (P < 0.001). Finally, the overall diagnostic image quality scores increased linearly with increasing IR strength level (P < 0.001). CONCLUSION: The optimal strength level of IR in low-dose cervical spine MDCT depends on the anatomical structure to be analyzed. For the intervertebral discs and the content of neural foramina, high strength levels of IR are recommended.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Shaping the interaction landscape of bioactive molecules.

MOTIVATION: Most bioactive molecules perform their action by interacting with proteins or other macromolecules. However, for a significant fraction of them, the primary target remains unknown. In addition, the majority of bioactive molecules have more than one target, many of which are poorly characterized. Computational predictions of bioactive molecule targets based on similarity with known ligands are powerful to narrow down the number of potential targets and to rationalize side effects of known molecules. RESULTS: Using a reference set of 224 412 molecules active on 1700 human proteins, we show that accurate target prediction can be achieved by combining different measures of chemical similarity based on both chemical structure and molecular shape. Our results indicate that the combined approach is especially efficient when no ligand with the same scaffold or from the same chemical series has yet been discovered. We also observe that different combinations of similarity measures are optimal for different molecular properties, such as the number of heavy atoms. This further highlights the importance of considering different classes of similarity measures between new molecules and known ligands to accurately predict their targets. CONTACT: olivier.michielin@unil.ch or vincent.zoete@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dispersal routes reconstruction and the minimum cost arborescence problem.

We show that the dispersal routes reconstruction problem can be stated as an instance of a graph theoretical problem known as the minimum cost arborescence problem, for which there exist efficient algorithms. Furthermore, we derive some theoretical results, in a simplified setting, on the possible optimal values that can be obtained for this problem. With this, we place the dispersal routes reconstruction problem on solid theoretical grounds, establishing it as a tractable problem that also lends itself to formal mathematical and computational analysis. Finally, we present an insightful example of how this framework can be applied to real data. We propose that our computational method can be used to define the most parsimonious dispersal (or invasion) scenarios, which can then be tested using complementary methods such as genetic analysis.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.