Éditeur(s) : HAL CCSD Inter-Research
Résumé : Precise knowledge of lifetime migrations is vital in exploited fish species, since all essential habitats must be protected to maintain sustainable stock levels. The present study used multi-element otolith fingerprints of the gilthead sea bream Sparus aurata (L.) to discriminate its main juvenile and adult habitats in the Languedoc-Roussillon region (Gulf of Lions, northwest Mediterranean) and infer the lifetime migrations of 12 individuals from the area (11 from the present day and 1 from the Roman era). This allowed for the first time the identification of key habitats for the successful completion of the species' life cycle in the Gulf of Lions, and the connectivity between them. Our results revealed that lagoon use by S. aurata is probably ancient (>2500 yr) and confirmed its current commonness. Yet, although most observed migration patterns were in accordance with the migratory behavior previously described for the species, strong inter-individual variations and new patterns in habitat use were detected. At the juvenile stage, a preference for shallow lagoons with low salinities was evidenced. Nevertheless, the first year of life can also be successfully completed in marine conditions. At the adult stage, lagoon use was shown to occur until at least age 4 yr, with periods of lagoon residency of up to 11 mo in a year, often including winter months. Because overwintering in the lagoons was previously thought to be impossible for S. aurata due to low temperatures, this finding has important implications for future stock management, especially since the species breeds in winter.
Marine Ecology Progress Series

hal-00682003
https://hal.archives-ouvertes.fr/hal-00682003
DOI : 10.3354/meps09444

Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
LiDAR (Light Detection And Ranging) remote sensing has been shown to be a good technique for the estimation of forest parameters such as canopy heights and above ground biomass. Whilst airborne LiDAR data are in general very dense but only available over small areas due to the cost of their acquisition, spaceborne LiDAR data acquired from the Geoscience Laser Altimeter System (GLAS) have a coarser acquisition density associated with a global cover. It is therefore valuable to analyze the integration relevance of canopy heights estimated from LiDAR sensors with ancillary data such as geological, meteorological, and phenological variables in order to propose a forest canopy height map with good precision and high spatial resolution.In this study, canopy heights extracted from both airborne and spaceborne LiDAR, were first extrapolated from available environmental data (e.g. geology, slope, vegetation indices, etc.). The estimated canopy height maps using random forest (RF) regression from the airborne or GLAS calibration datasets showed similar precisions (RMSE better than 6.5 m). In order to improve the precision of the canopy height estimates regression-kriging (kriging of random forest regression residuals) was used. Results indicated an improvement in the RMSE (decrease from 6.5 to 4.2 m) for the regression-kriging maps from the GLAS dataset, and from 5.8 to 1.8 m for the regression-kriging map from the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on the precision of canopy height estimates, six subsets were derived from the initial airborne LiDAR dataset with flight line spacing of 5, 10, 20, 30, 40 and 50 km (corresponding to 0.29, 0.11, 0.08, 0.05, 0.04, and 0.03 points/km² respectively). Results indicated that using the regression-kriging approach achieved a precision of 1.8 m on the canopy height map with flight line spacing of 5 km and achieved an average RMSE of 4.8m for the configuration for the 50 km flight line spacing.
ISSN: 2072-4292

hal-01361343
https://hal.archives-ouvertes.fr/hal-01361343
https://hal.archives-ouvertes.fr/hal-01361343/document
https://hal.archives-ouvertes.fr/hal-01361343/file/mt2016-pub00048036.pdf
DOI : 10.3390/rs8030240

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : We examined tree-soil habitat associations in lowland forest communities at Paracou, French Guiana. We analyzed a large dataset assembling six permanent plots totaling 37.5 ha, in which extensive LIDAR-derived topographical data and soil chemical and physical data have been integrated with precise botanical determinations. Map of relative elevation from the nearest stream summarized both soil fertility and hydromorphic characteristics, with seasonally inundated bottomlands having higher soil phosphate content and base saturation, and plateaus having higher soil carbon, nitrogen and aluminum contents. We employed a statistical test of correlations between tree species density and environmental maps, by generating Monte Carlo simulations of random raster images that preserve autocorrelation of the original maps. Nearly three fourths of the 94 taxa with at least one stem per ha showed a significant correlation between tree density and relative elevation, revealing contrasted species-habitat associations in term of abundance, with seasonally inundated bottomlands (24.5% of species) and well-drained plateaus (48.9% of species). We also observed species preferences for environments with or without steep slopes (13.8% and 10.6%, respectively). We observed that closely-related species were frequently associated with different soil habitats in this region (70% of the 14 genera with congeneric species that have a significant association test) suggesting species-habitat associations have arisen multiple times in this tree community. We also tested if species with similar habitat preferences shared functional strategies. We found that seasonally inundated forest specialists tended to have smaller stature (maximum diameter) than species found on plateaus. Our results underline the importance of tree-soil habitat associations in structuring diverse communities at fine spatial scales and suggest that additional studies are needed to disentangle community assembly mechanisms related to dispersal limitation, biotic interactions and environmental filtering from species-habitat associations. Moreover, they provide a framework to generalize across tropical forest sites.
ISSN: 1932-6203

hal-01260289
https://hal.archives-ouvertes.fr/hal-01260289
PRODINRA : 342930
DOI : 10.1371/journal.pone.0141488

Éditeur(s) : HAL CCSD Ecological Society of America
Résumé : Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical method used to assign fish to unknown origin. Among the available methods of classification, Linear Discriminant Analysis (LDA) is the most frequently used, although it assumes data are multivariate normal with homogeneous within-group dispersions, conditions that are not always met by otolith chemical data, even after transformation. Other less constrained classification methods are available, but there is a current lack of comparative analysis in applications to otolith microchemistry. Here, we assessed stock identification accuracy for four classification methods (LDA, Quadratic Discriminant Analysis [QDA], Random Forests [RF], and Artificial Neural Networks [ANN]), through the use of three distinct data sets. In each case, all possible combinations of chemical elements were examined to identify the elements to be used for optimal accuracy in fish assignment to their actual origin. Our study shows that accuracy differs according to the model and the number of elements considered. Best combinations did not include all the elements measured, and it was not possible to define an ad hoc multielement combination for accurate site discrimination. Among all the models tested, RF and ANN performed best, especially for complex data sets (e. g., with numerous fish species and/or chemical elements involved). However, for these data, RF was less time-consuming and more interpretable than ANN, and far more efficient and less demanding in terms of assumptions than LDA or QDA. Therefore, when LDA and QDA assumptions cannot be reached, the use of machine learning methods, such as RF, should be preferred for stock assessment and nursery identification based on otolith microchemistry, especially when data set include multispecific otolith signatures and/or many chemical elements.
ISSN: 1051-0761

hal-00644549
https://hal.archives-ouvertes.fr/hal-00644549
DOI : 10.1890/09-1887.1

Éditeur(s) : HAL CCSD
Résumé : IGARSS 2015, Milan, ITA, 26-/07/2015 - 31/07/2015
International audience
LiDAR remote sensing has been shown to be a good technique for the estimation of forest parameters such as canopy heights and aboveground biomass. Whilst airborne LiDAR data are in general very dense but only available over small areas due to the cost of their acquisition, spaceborne LiDAR data acquired from the Geoscience Laser Altimeter System (GLAS) have a coarser acquisition density associated with a global cover. It is therefore valuable to analyze the integration relevance of canopy heights estimated from LiDAR sensors with ancillary data such as geological, meteorological, and phenological variables in order to propose a forest canopy height map with good precision and high spatial resolution.In this study, canopy heights extracted from both airborne and spaceborne LiDAR, were first extrapolated from available environmental data. The estimated canopy height maps using random forest (RF) regression from the airborne or GLAS calibration datasets showed similar precisions (RMSE better than 6.5 m). In order to improve the precision of the canopy height estimates regression-kriging (kriging of RF regression residuals) was used. Results indicated an improvement in the RMSE (decrease from 6.5 to 4.2 m) for the regression-kriging maps from the GLAS dataset, and from 5.8 to 1.8 m for the regression-kriging map from the airborne LiDAR dataset.
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Milan, Italy

hal-01244677
https://hal.archives-ouvertes.fr/hal-01244677
https://hal.archives-ouvertes.fr/hal-01244677/document
https://hal.archives-ouvertes.fr/hal-01244677/file/mt2015-pub00044297.pdf
DOI : 10.1109/IGARSS.2015.7326729

Éditeur(s) : HAL CCSD
Résumé : For ecology scientists, spatial statistics are a set of tools allowing characterization of the structure of a point set, for instance a map of trees in a forest plot. This structure is defined implicitly as a departure from complete spatial randomness (CSR), the result of a Poisson point process. Inhomogeneity of the process and non-independence of points are its causes. As they cannot be disentangled by analyzing the data, so-called "spatial concentration" or "aggregation" (evenness due to repulsion also exists but is actually rare) usually concerns non-independence while intensity is assumed as known. The literature of point processes and measures of spatial structures is reviewed to clarify concepts and choices. The purpose of this thesis was to produce methodological enhancements. Its main results are: * A test for the most used statistic, Ripley's K function, against the null hypothesis of CSR. It can replace Monte-Carlo simulations used until now in the literature. * An extension of K to inhomogeneous processes, within a typology of available statistics (absolute, relative and topographic measures). When data is available as number of objects per zones (say a number of tree in each forest plot) rather than their exact position, information theory is used to define a general framework allowing to characterize spatial structure (of species) and diversity (of plots) as two aspects of a single measure of inequality. This framework is applied to Shannon's index of biodiversity to derive a self-sufficient definition of beta diversity, its calculation independently from the difference between gamma and alpha diversity, and a statistical test of significance against the null hypothesis that plots are samples of the same community. The way is paved for other applications to measures of diversity and spatial structures. As a conclusion, it appears clear that pattern characterization tools are a first step to deal with ecological questionings. Their development is still a matter of research. Yet, they are far from sufficient to address ecological processes as point processes ignore the temporal aspect of object locations.
Les statistiques spatiales sont pour les écologues un ensemble d'outils permettant de caractériser la structure d'un semis de points, par exemple une carte représentant des emplacements des arbres dans une parcelle de forêt. Cette structure est définie implicitement comme un écart à semis complètement aléatoire, résultat d'un processus de Poisson. L'hétérogénéité du processus ponctuel dont le semis de points est une réalisation et la non-indépendance des points en sont les causes indiscernables, ce qui amène généralement à supposer l'intensité du processus connu et nommer " concentration spatiale " ou " agrégation " (la régularité spatiale est possible, mais rare en pratique) la non-indépendance. Une revue de la littérature des processus ponctuels et des mesures de structures spatiales est fournie pour clarifier les concepts et les choix. L'objectif de ce travail de thèse était de produire des améliorations méthodologiques. Ses résultats principaux sont : * L'établissement d'un test pour la principale statistique utilisée, la fonction K de Ripley, permettant de s'affranchir de la méthode de Monte-Carlo utilisée dans la littérature pour rejeter l'hypothèse nulle d'un processus complètement aléatoire. * L'extension de K aux processus hétérogènes, dans le cadre d'une typologie claire des statistiques (absolues, relatives, topographiques). Lorsque la position exacte des objets n'est pas connue, mais que des effectifs par zone sont disponibles (par exemple des nombres d'arbres par parcelle), la théorie de l'information est utilisée pour définir un cadre général permettant de caractériser la structure spatiale (des espèces dans les parcelles) et la diversité (des parcelles, en termes d'espèces) comme deux aspects d'une même mesure d'inégalité. Ce cadre est appliqué à l'indice de biodiversité de Shannon pour définir clairement la mesure de diversité bêta, son calcul direct indépendamment de la différence entre diversités gamma et alpha, et fournir un test statistique de non nullité. La voie est ouverte pour l'application à d'autres mesures de diversité et de structure spatiale. En conclusion, il semble clair que ces outils de caractérisation sont un premier pas pour traiter les questions écologiques, leur développement étant toujours du domaine de la recherche. Ils sont cependant très insuffisants pour répondre à des questions liées aux processus écologiques, assez éloignés des processus ponctuels qui ignorent l'aspect temporel de l'installation des objets.
https://pastel.archives-ouvertes.fr/pastel-00540327

NNT : 2010AGPT0075
pastel-00540327
https://pastel.archives-ouvertes.fr/pastel-00540327
https://pastel.archives-ouvertes.fr/pastel-00540327/document
https://pastel.archives-ouvertes.fr/pastel-00540327/file/13_Marcon2010.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
Ripley’s K function is the classical tool to characterize the spatial structure of point patterns. It is widely used in vegetation studies. Testing its values against a null hypothesis usually relies on Monte-Carlo simulations since little is known about its distribution.We introduce a statistical test against complete spatial randomness (CSR). The test returns the p-value to reject the null hypothesis of independence between point locations. It is more rigorous and faster than classical Monte-Carlo simulations. We show how to apply it to a tropical forest plot. The necessary R code is provided.
International Scholarly Research Network, ISRN Ecology

hal-01502637
https://hal-agroparistech.archives-ouvertes.fr/hal-01502637
https://hal-agroparistech.archives-ouvertes.fr/hal-01502637/document
https://hal-agroparistech.archives-ouvertes.fr/hal-01502637/file/2013_Marcon_Hindawi%20Publishing%20Corporation_%7B7A602F34-6983-47DE-924B-7CDC3B8D14F7%7D.pdf
DOI : 10.1155/2013/753475

Éditeur(s) : HAL CCSD
Résumé : International audience
We examined fine-scale heterogeneity of environmental conditions in a primary rain forest in French Guiana to describe variation in microhabitats that plants may experience during establishment. We characterized both the range as well as the spatial structuring of 11 environmental factors important for seedling establishment in six hexagonal sampling grids, one each in gap and understory sites at three points representing the predominant geomorphic units in this primary forest. Each grid contained 37 sampling points separated by 31 cm-20 m. Monte-Carlo tests of semivariograms against complete spatial randomness indicated that for many variables in all six sampling grids, spatial dependence did not exceed 1 m. A principal component analysis of all sampling points revealed a lack of spatial microhabitat structure, rather than homogeneous patches associated with canopy structure or geomorphology. Our results suggest that ample fine-scale spatial heterogeneity exists to support the coexistence of plant species with differential abiotic requirements for regeneration.
Botropica

halsde-00520179
https://hal.archives-ouvertes.fr/halsde-00520179
DOI : 10.1111/j.1744-7429.2009.00620.x

Éditeur(s) : HAL CCSD Elsevier
Résumé :  
The within-population spatial structure of genetic diversity is shaped by demographic processes, including historical accidents such as forest perturbations. Information drawn from the analysis of the spatial distribution of genetic diversity is therefore inherently linked to demographic-historical processes that ultimately determine the fate of populations. All adult trees and saplings in a 1.4-ha plot within a mixed Norway spruce (Picea abies [L.] Karst) stand were characterised by means of chloroplast (paternally inherited) markers, and a large sub-sample of these were genotyped at mitochondrial (maternally inherited) molecular markers. These data were used to analyse the spatial distribution of genetic variation and to compare the patterns corresponding to the two marker types. The plot presented non-homogeneous local stem density in the younger cohorts, and the indirect effect of this source of variation on the spatial genetic structure was investigated. Results suggest that (i) spatially limited seed dispersal induced patchiness in genotype distribution, while pollen flow had a homogenising effect; (ii) deviations from random spatial structure were stronger in the demographically most stable portions of the stand, while they were weaker where sudden bursts of regeneration occurred; (iii) spatially overlapping adult and sapling cohorts displayed the same spatial genetic structure (stronger on stable areas, weaker in portions of the stand undergoing events of intense regeneration), which was substantiated by the influence of local demographic processes. Regeneration dynamics as modulated by demography thus influences the distribution of genetic diversity within the stand both in the younger life stages and in the adult population.
ISSN: 0378-1127

hal-01032063
https://hal.archives-ouvertes.fr/hal-01032063
DOI : 10.1016/j.foreco.2008.03.023

Éditeur(s) : HAL CCSD
Résumé : Diffusion du document : INRA Documentation de Centre, Domaine de Duclos, 97170 Petitt-Bourg (Guadeloupe, France) Diplôme : DEA
il s'agit d'un type de produit dont les métadonnées ne correspondent pas aux métadonnées attendues dans les autres types de produit : DISSERTATION
Because soil respiration representes 80% of ecosystem respiration, it is a major flux between biosphere and atmosphere. We examined the effects of root and litter exclusion on soil CO! efflux (Rsu1) using trenching and litter exclusion in a tropical plantation constituted of trees seedlings installed in 16 mono-specific stands 20 years ago near Kourou, French Guyana. Soil CO2 efflux was measured using an infra red gas analyser (PP System,EGM4 ) at 16 randomly distributed plot in each treatment: control, root exclusion, litter exclusion and both root and litter exclusion. in the plantation. We measured R'1l1during four periods, and we have collected soil samples, litter biomass and measured moisture at 5 cm depth in the soil. Soil CO, efflux varied significantly among species from 2,8±O,7f1mo l. m''. s' (mean ± standard deviation) to 7.4± 1.7fLmol. n'-' . s ' for Qualea rosea and Vochys ia tomentosa, respectively. 1'0 significant correlation was found between RSIlI variability and soil moisture, which is mostly related to soil texture in the experimental site. Soil CO2 efflux was significantly reduced in litter exclusion treatment and root exclusion plots (6 months litter and/or root exclusion) during ail measurements period and for ail species, compared to control plots. The reduction of soil CO, efflux was higher in plot without root than in plot without litter of control plot (42% and 25%, respectively). There was an import ant specific diversity in these reductions . We estimated the contribution of roof respiration (Rr) to total Rso1 by calculating the difference between Rso1 control and Rsn l root exclusion plot corrected for the decomposition of root that were killed following t re n e h in ~. Thus the heterotrophic component of soil carbon efflux accounts for 46% of total carbon efflux (1,9f1 mol. rn" . s•') while root respiration accounts for 54% of soil carbon release (2,3 ~t mo l. m-2 S-I) . Because there was a negative and significant correlation between microbial respiration (Rrn) and C/N of mature leaves it seemed to be possible to predict Rm if we known the mature leaves quality. In addition a good estimate theorical R ~, values from R~, measured in different treatments.
La respiration du sol en représentant une part de 80% de la respiration de l'écosystème apparaît être un flux majeur entre la biosphère et l'atmosphère. Nous avons étudié les effets de l'exclusion racinaire et de la litière sur le flux de CO, du sol (R ~ , ) en utilisant la méthode de " Trench-plots" et de suppression de litière dans une plantation d'arbres tropicaux. Ces arbres, âgés de 20 ans ont été plantés sur un sol uniforme, près de Kourou en Guyane française, en 16 placeaux mono-spécifiques. Pour mesurer les flux de CO2 provenant du sol, nous avons utilisé un analyseur différentiel de gaz infrarouge portable muni d'une chambre. Les mesures ont été faites sur 4 traitements différents tels que : le contrôle, l'exclusion racinaire, l'exclusion de litière et l'exclusion de litière et de racine et ce, répétés sur chacune des 16 placettes mono-spécifiques. Cette étude comporte 4 campagnes de mesures. Nous avons également effectué des prélèvements de sol de litière et nous avons fait des mesures d’humidité de sol à une profondeur de 5 cm. Les flux de C01 du sol varient fortement entre espèces de 2.8±O.7 ~t m o 1. m-2. sol à 7 A± 1. 7 ~t m o l. m•1 sol pour Qua/ev rosea ct Vochysto tomentasa, respectivement. Il n'existe pas de corrélation significative entre les variations de Rw l ct celles de l'humidité du sol (indication sur la texture du sol de la plantation ). Nous avons observé que Rso1 était significativement plus faible dans les placeaux sans racines et/ou sans litière (6 mois après la mise en place de l'expérimentation) pour toutes les campagnes de mesures et pour toutes les espèces que dans les placeaux contrôlés. Cette réduction du flux de CO2 du sol est plus forte dans les "trench-plots " que dans les traitement s d'exclusion de litière avec 42 et 25% respectivement. Un effet "traitement " et un effet "espèce" important expliquent 3 1"/.. ct 13% de la variabilité totale de R~. Nous avons cherché à connaître la contribution des racines dans les valeurs de R""I. en comparant le flux de CO2 provenant du sol sur des "trench -plot s'' au flux de COl provenant du sol dans les placeaux contrôlés . Cette estimation a été corrigée pour prendre en compte la décomposition des racines tuées par les tranchées. Ainsi, la composante appartenant aux micro -organismes représente 46% du flux total de carbone provenant du sol (1.9Jlmo l. m-2 S•I ) alors que la respiration des racines représente 54% du dégagement de carbone (2 ,3~lmol. m ol . 5-La respiration des micro-organismes pourrait être estimée en mesurant le C/N des feuilles matures puisqu'il existe une corrélation significative et négative entre les deux. Enfin les résultats obtenus sur les différents traitements permettent d'obtenir une bonne estimation de la respiration du sol avec un RSIlI théorique corrélé à 66% avec les valeurs réelles mesurées.
https://hal.archives-ouvertes.fr/hal-01189239

hal-01189239
https://hal.archives-ouvertes.fr/hal-01189239
PRODINRA : 18212