Mud bank colonization by opportunistic mangroves: A case study from French Guiana using lidar data

Mud bank colonization by mangroves on the Amazon-influenced coast of French Guiana was studied using light detection and ranging (lidar) data which provide unique information on canopy geometry an sub-canopy topography. The role of topography was assessed through analysis of vegetation characteristics derived from these data. Measurements and analyses of mangrove expansion rates over space and time led to the identification of two distinct colonization processes. The first involves regular step-by-step mangrove expansion to the northwest of the experimental site. The second is qualified as ‘opportunistic’ since it involves a clear relationship between specific ecological characteristics of pioneer Avicennia and mud cracks affecting the mud bank surface and for which probabilities of occurrence were computed from terrain elevations. It is argued from an original analysis of the latter relationship that mud cracks cannot be solely viewed as water stress features that reflect desiccation potentially harmful to plant growth. Indeed, our results tend to demonstrate that they significantly enhance the propensity for mangroves to anchor and take root, thus leading to the colonization of tens of hectares in a few days. The limits and potential of lidar data are discussed with reference to the study of muddy coasts. Finally, the findings of the study are reconsidered within the context of a better understanding of both topography and vegetation characteristics on mangrove-fringed muddy coasts

Biomass prediction in tropical forests : the canopy grain approach

18 pagesThe challenging task of biomass prediction in dense and heterogeneous tropical forest requires a multi-parameter and multi-scale characterization of forest canopies. Completely different forest structures may indeed present similar above ground biomass (AGB) values. This is probably one of the reasons explaining why tropical AGB still resists accurate mapping through remote sensing techniques. There is a clear need to combine optical and radar remote sensing to benefit from their complementary responses to forest characteristics. Radar and Lidar signals are rightly considered to provide adequate measurements of forest structure because of their capability of penetrating and interacting with all the vegetation strata. However, signal saturation at the lowest radar frequencies is observed at the midlevel of biomass range in tropical forests (Mougin et al. 1999; Imhoff, 1995). Polarimetric Interferometric (PolInsar) data could improve the inversion algorithm by injecting forest interferometric height into the inversion of P-band HV polarization signal. Within this framework, the TROPISAR mission, supported by the Centre National d'Etudes Spatiales (CNES) for the preparation of the European Space Agency (ESA) BIOMASS program is illustrative of both the importance of interdisciplinary research associating forest ecologists and physicists and the importance of combined measurements of forest properties. Lidar data is a useful technique to characterize the vertical profile of the vegetation cover (e.g. Zhao et al. 2009) which in combination with radar (Englhart et al. 2011) or optical (e.g. Baccini et al. 2008; Asner et al. 2011) and field plot data may allow vegetation carbon stocks to be mapped over large areas of tropical forest at different resolution scales ranging from 1 hectare to 1 km². However, small-footprint Lidar data are not yet accessible over sufficient extents and with sufficient revisiting time because its operational use for tropical studies remains expensive. At the opposite, very-high (VHR) resolution imagery, i.e. approximately 1-m resolution, provided by recent satellite like Geoeye, Ikonos, Orbview or Quickbird as well as the forthcoming Pleiades becomes widely available at affordable costs, or even for free in certain regions of the world through Google Earth®. Compared to coarser resolution imagery with pixel size greater than 4 meters, VHR imagery greatly improves thematic information on forest canopies. Indeed, the contrast between sunlit and shadowed trees crowns as visible on such images (Fig. 1) is potentially informative on the structure of the forest canopy while new promising methods now exist for analyzing these fine scale satellite observations (e.g. Bruniquel-Pinel & Gastellu-Etchegorry, 1998; Malhi & Roman-Cuesta, 2008; Rich et al. 2010). Besides, we believe that there is also a great potential in similarly using historical series of digitized aerial photographs that proved to be useful in the past for mapping large extents of unexplored forest (Le Touzey, 1968; Richards, 1996) for quantifying AGB changes through time. This book chapter presents the advancement of a research program undertaken by our team for estimating high biomass mangrove and terra firme forests of Amazonia using canopy grain from VHR images (Couteron et al. 2005; Proisy et al. 2007; Barbier et al., 2010; 2011). We present in a first section, the canopy grain notion and the fundamentals of the Fourier-based Textural Ordination (FOTO) method we developed. We then introduce a dual experimental-theoretical approach implemented to understand how canopy structure modifies the reflectance signal and produces a given texture. We discuss, for example, the influence of varying sun-view acquisition conditions on canopy grain characteristics. A second section assesses the potential and limits of the canopy grain approach to predict forest stand structure and more specifically above ground biomass. Perspectives for a better understanding of canopy grain-AGB relationships conclude this work

Tree crown detection in high resolution optical and LiDAR images of tropical forest

International audienceTropical forests are complex ecosystems where the potential of remote sensing has not yet been fully realized. The increasing availability of satellite metric imagery along with canopy altimetry from airborne LiDAR open new prospects to detect individual trees. For this objective, we optimized, calibrated and applied a model based on marked point processes to detect trees in high biomass mangroves of French Guiana by considering a set of 1m pixel images including 1) panchromatic images from the IKONOS sensor 2) LiDAR-derived canopy 2D altimetry and 3) reflectance panchromatic images simulated by the DART-model. The relevance of detection is then discussed considering: (i) the agreement in space of detected crown centers locations with known true locations for the DART images and also the detection agreement for each pair of IKONOS and LiDAR images, and (ii) the comparison between the frequency distributions of the diameters of the detected crowns and of the tree trunks measured in the field. Both distributions are expected to be related due to the allometry relationships between trunk and crown

Extending the clinical spectrum of X-linked Tonne-Kalscheuer syndrome (TOKAS):new insights from the fetal perspective

INTRODUCTION: Tonne-Kalscheuer syndrome (TOKAS) is a recessive X-linked multiple congenital anomaly disorder caused by RLIM variations. Of the 41 patients reported, only 7 antenatal cases were described.METHOD: After the antenatal diagnosis of TOKAS by exome analysis in a family followed for over 35 years because of multiple congenital anomalies in five male fetuses, a call for collaboration was made, resulting in a cohort of 11 previously unpublished cases.RESULTS: We present a TOKAS antenatal cohort, describing 11 new cases in 6 French families. We report a high frequency of diaphragmatic hernia (9 of 11), differences in sex development (10 of 11) and various visceral malformations. We report some recurrent dysmorphic features, but also pontocerebellar hypoplasia, pre-auricular skin tags and olfactory bulb abnormalities previously unreported in the literature. Although no clear genotype-phenotype correlation has yet emerged, we show that a recurrent p.(Arg611Cys) variant accounts for 66% of fetal TOKAS cases. We also report two new likely pathogenic variants in RLIM, outside of the two previously known mutational hotspots.CONCLUSION: Overall, we present the first fetal cohort of TOKAS, describe the clinical features that made it a recognisable syndrome at fetopathological examination, and extend the phenotypical spectrum and the known genotype of this rare disorder.</p

Structure-Guided Evolution of Potent and Selective CHK1 Inhibitors through Scaffold Morphing

Pyrazolopyridine inhibitors with low micromolar potency for CHK1 and good selectivity against CHK2 were previously identified by fragment-based screening. The optimization of the pyrazolopyridines to a series of potent and CHK1-selective isoquinolines demonstrates how fragment-growing and scaffold morphing strategies arising from a structure-based understanding of CHK1 inhibitor binding can be combined to successfully progress fragment-derived hit matter to compounds with activity in vivo. The challenges of improving CHK1 potency and selectivity, addressing synthetic tractability, and achieving novelty in the crowded kinase inhibitor chemical space were tackled by multiple scaffold morphing steps, which progressed through tricyclic pyrimido[2,3-b]azaindoles to N-(pyrazin-2-yl)pyrimidin-4-amines and ultimately to imidazo[4,5-c]pyridines and isoquinolines. A potent and highly selective isoquinoline CHK1 inhibitor (SAR-020106) was identified, which potentiated the efficacies of irinotecan and gemcitabine in SW620 human colon carcinoma xenografts in nude mice

Multiparameter Lead Optimization to Give an Oral Checkpoint Kinase 1 (CHK1) Inhibitor Clinical Candidate: (R)-5-((4-((Morpholin-2-ylmethyl)amino)-5-(trifluoromethyl)pyridin-2-yl)amino)pyrazine-2-carbonitrile (CCT245737)

Multiparameter optimization of a series of 5-((4-aminopyridin-2-yl)amino)pyrazine-2-carbonitriles resulted in the identification of a potent and selective oral CHK1 preclinical development candidate with in vivo efficacy as a potentiator of deoxyribonucleic acid (DNA) damaging chemotherapy and as a single agent. Cellular mechanism of action assays were used to give an integrated assessment of compound selectivity during optimization resulting in a highly CHK1 selective adenosine triphosphate (ATP) competitive inhibitor. A single substituent vector directed away from the CHK1 kinase active site was unexpectedly found to drive the selective cellular efficacy of the compounds. Both CHK1 potency and off-target human ether-a-go-go-related gene (hERG) ion channel inhibition were dependent on lipophilicity and basicity in this series. Optimization of CHK1 cellular potency and in vivo pharmacokinetic–pharmacodynamic (PK–PD) properties gave a compound with low predicted doses and exposures in humans which mitigated the residual weak in vitro hERG inhibition

Linking remote-sensing information to tropical forest structure : the crucial role of modelling

fdi:010055313International audienceUsing remote sensing to provide reliable information over extensive areas of dense and heterogeneous tropical forests is a challenging task. Not only is the task challenging, but it also has become closely related to global concerns about reducing greenhouse gas emissions from deforestation and forest degradation, also known as the REDD process. The AMAP laboratory in Montpellier, France, is contributing to this challenge at the interface between signal processing and plant and vegetation modelling which is its central domain of expertise. Models of forest structure are an important tool to fill the scale gap between field observations and remotely sensed information. They help also to understand the complex interactions between signal and forest vegetation. As remotely-sensed data are diversifying, coupling forest structure and radiative transfer models helps to translate signal information into biophysical parameters. Refining such an approach is needed to design replicable methods that address the most challenging aspect of monitoring spatiotemporal variations of stand structure in forest types retaining high aboveground biomass

Bidirectional texture function of high resolution optical images of tropical forest : an approach using LiDAR hillshade simulations

Quantifying and monitoring the structure and degradation of tropical forests over regional to global scales is gaining increasing scientific and societal importance. Reliable automated methods are only beginning to appear; for instance, through the recent development of textural approaches applied to high resolution optical imagery. In particular, the Fourier Transform Textural Ordination (FOTO) method shows some potential to provide non-saturating estimates of tropical forest structure, including for large scale applications. However, we need to understand more precisely how canopy structure interacts with physical signals (light) to produce a given texture, notably to assess the method's sensitivity to varying sun-view acquisition conditions. In this study, we take advantage of the detailed description of canopy topography provided by airborne small footprint LiDAR data acquired over the Paracou forest experimental station in French Guiana. Using hillshade models and a range of sun-view angles identical to the actual parameter distributions found for Quickbird (TM) images over the Amazon, we study noise and bias in texture estimation induced by the changing configurations. We introduce the bidirectional texture function, which summarizes these effects, and in particular the existence of a textural 'hot spot', similar to a well-known feature of bidirectional reflectance studies. For texture, this effect implies that coarseness decreases in configurations for which shadows are concealed to the observer. We also propose a method, termed partitioned standardization, that allows mitigating acquisition effects and discuss the potential for an operational use of VHR optical imagery and the FOTO method in the current context of international decisions to reduce CO2 emissions due to deforestation and forest degradation

Suivi des mangroves par télédétection optique à très haute résolution spatiale

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Linking canopy images to forest structural parameters : potential of a modeling framework

Context Remote sensing methods, and in particular very high (metric) resolution optical imagery, are essential assets to obtain forest structure data that cannot be measured from the ground because they are too difficult to measure or because the areas to sample are too large or inaccessible. Aim To understand what kind of, and how precisely and accurately, information on forest structure can be inverted from RS data, we propose a modeling framework allowing to produce forest canopy images for any type of forest based on basic inventory data. Methods This framework combines a simple 3D forest model named "Allostand," based on empirically or theoretically derived diameter at breast height distributions and allometry rules, with a well-established radiative transfer model, discrete anisotropic radiative transfer. Results Resulting simulated images appear of good realism for textural analysis. The potential of the approach for the development of quantitative methods to assess forest structure, dynamics, matter and energy budgets, and degradation, including in tropical contexts, is illustrated emphasizing broad-leaved natural forests. Conclusion Consequently, this theoretical framework appears as a valuable component for developing inversion methods from canopy images and studying their sensitivity to structural and instrumental effects