Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

Impacts of climate change and species distribution modelling: future scenarios to endangered species in South Brazil.

Earth climate has changed significantly in the last century and the different models indicate that it will continue to change over the next decades, even if the emission of greenhouse gases stop immediately. These changes have impact on different plant populations, as well as in the actual distribution of several species. As plants, in general, have a smaller capacity of dispersion compared with the animals it is likely that they will suffer the impacts of the climate change more intensively.

Discrimination capacity in species distribution models depends on the representativeness of the environmental domain

Aim When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time,we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models.

New measures for assessing model equilibrium and prediction mismatch in species distribution models

Models based on species distributions are widely used and serve important purposes in ecology, biogeography and conservation. Their continuous predictions of environmental suitability are commonly converted into a binary classification of predicted (or potential) presences and absences, whose accuracy is then evaluated through a number of measures that have been the subject of recent reviews. We propose four additional measures that analyse observation-prediction mismatch from a different angle – namely, from the perspective of the predicted rather than the observed area – and add to the existing toolset of model evaluation methods. We explain how these measures can complete the view provided by the existing measures, allowing further insights into distribution model predictions. We also describe how they can be particularly useful when using models to forecast the spread of diseases or of invasive species and to predict modifications in species’ distributions under climate and land-use change

Impacts of climate change and species distribution modelling: future scenarios to endangered species in South Brazil.

2016

Patterns of Cactaceae species distribution in a protected area in the semiarid caatinga biome of North-Eastern Brazil.

2016

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.

Appendix 7: List of species with their distribution ranges restricted to the corresponding phytogeographical region

Understanding species distribution patterns and the corresponding environmental determinants is a crucial step in the development of effective strategies for the conservation and management of plant communities and ecosystems. Therefore, a central prerequisite is the biogeographical and macroecological analysis of factors and processes that determine contemporary, potential, as well as future geographic distribution of species. This thesis has been conducted in the framework of the BIOMAPS-BIOTA project at the Nees Institute of Biodiversity of Plants, which was funded by the German Federal Ministry of Education and Research (BMBF). The study investigated patterns of plants species richness and phytogeographic regions under contemporary environmental conditions and forecasted future climate change in the area of West Africa covering five countries: Benin, Burkina Faso, Côte d'Ivoire, Ghana and Togo. Firstly, geographic patterns of vascular plant species richness have been depicted at a relatively fine spatial resolution based on the potential distribution of 3,393 species. Species richness is closely related to the steep climatic gradient existing in the region with a high concentration of species in the most humid areas in the south and decreases towards the northern drier areas. The investigation of the effectiveness of the existing network of protected areas shows an overall good coverage of species in the study area. However, the proportion of covered species is considerably lower at national extent for some countries, thus calling for more protected areas in order to cover adequately a maximum number of plants species in these countries. Secondly, based on the potential distribution range of vascular plant species, seven phytogeographic regions have been delineated that broadly reflect the vegetation zones as defined by White (1983). However notable differences to the delineation of White (1983) occur at the margins of some regions. Corresponding to a general southward shifted of all regions. And expansion of the Sahel vegetation zone is observed in the north, while the rainforest zone is decreased in the very south.This is alarming since the rainforest shelters a high number of species and a high proportion of range-restricted or endemic species, despite their relatively small extent compared to the other regions. Finally, the evaluation of the potential impact of climate change on plant species richness in the study area, results in a severe loss of future suitable habitat for up to 50% of species per grid cell, particularly in the rainforest region. Moreover, the analysis of the possible shift of phytogeographic regions shows in general a strong deterioration of the West African rainforest. In contrast the drier areas are expanding continuously, although a slight gain in species number can be observed in some particular regions. The overall lesson to retain from the results of this study is that the West African rainforest should be fixed as a high priority area for the conservation of biodiversity of plants, since it is subject to severe contemporary and projected future threats.

Evidence of long-term changes in the distribution of key intertidal species

World Congress of Malacology, Ponta Delgada, July 22-28, 2013.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

Knowing the past to predict the future: land-use change and the distribution of invasive bullfrogs

Biological invasions and land-use changes are two major causes of the global modifications of biodiversity. Habitat suitability models are the tools of choice to predict potential distributions of invasive species. Although land-use is a key driver of alien species invasions, it is often assumed that land-use is constant in time. Here we combine historical and present day information, to evaluate whether land-use changes could explain the dynamic of invasion of the American bullfrog Rana catesbeiana (=Lithobathes catesbeianus) in Northern Italy, from the 1950s to present-day. We used maxent to build habitat suitability models, on the basis of past (1960s, 1980s) and present-day data on land-uses and species distribution. For example, we used models built using the 1960s data to predict distribution in the 1980s, and so on. Furthermore, we used land-use scenarios to project suitability in the future. Habitat suitability models predicted well the spread of bullfrogs in the subsequent temporal step. Models considering land-use changes predicted invasion dynamics better than models assuming constant land-use over the last 50 years. Scenarios of future land-use suggest that suitability will remain similar in the next years. Habitat suitability models can help to understand and predict the dynamics of invasions; however, land-use is not constant in time: land-use modifications can strongly affect invasions; furthermore, both land management and the suitability of a given land-use class may vary in time. An integration of land-use changes in studies of biological invasions can help to improve management strategies.

Anthropogenic influence on the distribution, abundance and diversity of sandfly species (Diptera: Phlebotominae: Psychodidae), vectors of cutaneous leishmaniasis in Panama

In Panama, species of the genus Lutzomyia are vectors of American cutaneous leishmaniasis (ACL). There is no recent ecological information that may be used to develop tools for the control of this disease. Thus, the goal of this study was to determine the composition, distribution and diversity of Lutzomyia species that serve as vectors of ACL. Sandfly sampling was conducted in forests, fragmented forests and rural environments, in locations with records of ACL. Lutzomyia gomezi, Lutzomyia panamensis and Lutzomyia trapidoi were the most widely distributed and prevalent species. Analysis of each sampling point showed that the species abundance and diversity were greatest at points located in the fragmented forest landscape. However, when the samples were grouped according to the landscape characteristics of the locations, there was a greater diversity of species in the rural environment locations. The Kruskal Wallis analysis of species abundance found that Lu. gomezi and Lu. trapidoi were associated with fragmented environments, while Lu. panamensis, Lutzomyia olmeca bicolor and Lutzomyia ylephiletor were associated with forested environments. Therefore, we suggest that human activity influences the distribution, composition and diversity of the vector species responsible for leishmaniasis in Panama.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

Changing landscapes of Switzerland: assessing effects of historic and future land uses and land covers on the occurrence of selected butterfly species

Summary Landscapes are continuously changing. Natural forces of change such as heavy rainfall and fires can exert lasting influences on their physical form. However, changes related to human activities have often shaped landscapes more distinctly. In Western Europe, especially modern agricultural practices and the expanse of overbuilt land have left their marks in the landscapes since the middle of the 20th century. In the recent years men realised that mare and more changes that were formerly attributed to natural forces might indirectly be the result of their own action. Perhaps the most striking landscape change indirectly driven by human activity we can witness in these days is the large withdrawal of Alpine glaciers. Together with the landscapes also habitats of animal and plant species have undergone vast and sometimes rapid changes that have been hold responsible for the ongoing loss of biodiversity. Thereby, still little knowledge is available about probable effects of the rate of landscape change on species persistence and disappearance. Therefore, the development and speed of land use/land cover in the Swiss communes between the 1950s and 1990s were reconstructed using 10 parameters from agriculture and housing censuses, and were further correlated with changes in butterfly species occurrences. Cluster analyses were used to detect spatial patterns of change on broad spatial scales. Thereby, clusters of communes showing similar changes or transformation rates were identified for single decades and put into a temporally dynamic sequence. The obtained picture on the changes showed a prevalent replacement of non-intensive agriculture by intensive practices, a strong spreading of urban communes around city centres, and transitions towards larger farm sizes in the mountainous areas. Increasing transformation rates toward more intensive agricultural managements were especially found until the 1970s, whereas afterwards the trends were commonly negative. However, transformation rates representing the development of residential buildings showed positive courses at any time. The analyses concerning the butterfly species showed that grassland species reacted sensitively to the density of livestock in the communes. This might indicate the augmented use of dry grasslands as cattle pastures that show altered plant species compositions. Furthermore, these species also decreased in communes where farms with an agricultural area >5ha have disappeared. The species of the wetland habitats were favoured in communes with smaller fractions of agricultural areas and lower densities of large farms (>10ha) but did not show any correlation to transformation rates. It was concluded from these analyses that transformation rates might influence species disappearance to a certain extent but that states of the environmental predictors might generally outweigh the importance of the corresponding rates. Information on the current distribution of species is evident for nature conservation. Planning authorities that define priority areas for species protection or examine and authorise construction projects need to know about the spatial distribution of species. Hence, models that simulate the potential spatial distribution of species have become important decision tools. The underlying statistical analyses such as the widely used generalised linear models (GLM) often rely on binary species presence-absence data. However, often only species presence data have been colleted, especially for vagrant, rare or cryptic species such as butterflies or reptiles. Modellers have thus introduced randomly selected absence data to design distribution models. Yet, selecting false absence data might bias the model results. Therefore, we investigated several strategies to select more reliable absence data to model the distribution of butterfly species based on historical distribution data. The results showed that better models were obtained when historical data from longer time periods were considered. Furthermore, model performance was additionally increased when long-term data of species that show similar habitat requirements as the modelled species were used. This successful methodological approach was further applied to assess consequences of future landscape changes on the occurrence of butterfly species inhabiting dry grasslands or wetlands. These habitat types have been subjected to strong deterioration in the recent decades, what makes their protection a future mission. Four spatially explicit scenarios that described (i) ongoing land use changes as observed between 1985 and 1997, (ii) liberalised agricultural markets, and (iii) slightly and (iv) strongly lowered agricultural production provided probable directions of landscape change. Current species-environment relationships were derived from a statistical model and used to predict future occurrence probabilities in six major biogeographical regions in Switzerland, comprising the Jura Mountains, the Plateau, the Northern and Southern Alps, as well as the Western and Eastern Central Alps. The main results were that dry grasslands species profited from lowered agricultural production, whereas overgrowth of open areas in the liberalisation scenario might impair species occurrence. The wetland species mostly responded with decreases in their occurrence probabilities in the scenarios, due to a loss of their preferred habitat. Further analyses about factors currently influencing species occurrences confirmed anthropogenic causes such as urbanisation, abandonment of open land, and agricultural intensification. Hence, landscape planning should pay more attention to these forces in areas currently inhabited by these butterfly species to enable sustainable species persistence. In this thesis historical data were intensively used to reconstruct past developments and to make them useful for current investigations. Yet, the availability of historical data and the analyses on broader spatial scales has often limited the explanatory power of the conducted analyses. Meaningful descriptors of former habitat characteristics and abundant species distribution data are generally sparse, especially for fine scale analyses. However, this situation can be ameliorated by broadening the extent of the study site and the used grain size, as was done in this thesis by considering the whole of Switzerland with its communes. Nevertheless, current monitoring projects and data recording techniques are promising data sources that might allow more detailed analyses about effects of long-term species reactions on landscape changes in the near future. This work, however, also showed the value of historical species distribution data as for example their potential to locate still unknown species occurrences. The results might therefore contribute to further research activities that investigate current and future species distributions considering the immense richness of historical distribution data. Résumé Les paysages changent continuellement. Des farces naturelles comme des pluies violentes ou des feux peuvent avoir une influence durable sur la forme du paysage. Cependant, les changements attribués aux activités humaines ont souvent modelé les paysages plus profondément. Depuis les années 1950 surtout, les pratiques agricoles modernes ou l'expansion des surfaces d'habitat et d'infrastructure ont caractérisé le développement du paysage en Europe de l'Ouest. Ces dernières années, l'homme a commencé à réaliser que beaucoup de changements «naturels » pourraient indirectement résulter de ses propres activités. Le changement de paysage le plus apparent dont nous sommes témoins de nos jours est probablement l'immense retraite des glaciers alpins. Avec les paysages, les habitats des animaux et des plantes ont aussi été exposés à des changements vastes et quelquefois rapides, tenus pour coresponsable de la continuelle diminution de la biodiversité. Cependant, nous savons peu des effets probables de la rapidité des changements du paysage sur la persistance et la disparition des espèces. Le développement et la rapidité du changement de l'utilisation et de la couverture du sol dans les communes suisses entre les années 50 et 90 ont donc été reconstruits au moyen de 10 variables issues des recensements agricoles et résidentiels et ont été corrélés avec des changements de présence des papillons diurnes. Des analyses de groupes (Cluster analyses) ont été utilisées pour détecter des arrangements spatiaux de changements à l'échelle de la Suisse. Des communes avec des changements ou rapidités comparables ont été délimitées pour des décennies séparées et ont été placées en séquence temporelle, en rendrent une certaine dynamique du changement. Les résultats ont montré un remplacement répandu d'une agriculture extensive des pratiques intensives, une forte expansion des faubourgs urbains autour des grandes cités et des transitions vers de plus grandes surfaces d'exploitation dans les Alpes. Dans le cas des exploitations agricoles, des taux de changement croissants ont été observés jusqu'aux années 70, alors que la tendance a généralement été inversée dans les années suivantes. Par contre, la vitesse de construction des nouvelles maisons a montré des courbes positives pendant les 50 années. Les analyses sur la réaction des papillons diurnes ont montré que les espèces des prairies sèches supportaient une grande densité de bétail. Il est possible que dans ces communes beaucoup des prairies sèches aient été fertilisées et utilisées comme pâturages, qui ont une autre composition floristique. De plus, les espèces ont diminué dans les communes caractérisées par une rapide perte des fermes avec une surface cultivable supérieure à 5 ha. Les espèces des marais ont été favorisées dans des communes avec peu de surface cultivable et peu de grandes fermes, mais n'ont pas réagi aux taux de changement. Il en a donc été conclu que la rapidité des changements pourrait expliquer les disparitions d'espèces dans certains cas, mais que les variables prédictives qui expriment des états pourraient être des descripteurs plus importants. Des informations sur la distribution récente des espèces sont importantes par rapport aux mesures pour la conservation de la nature. Pour des autorités occupées à définir des zones de protection prioritaires ou à autoriser des projets de construction, ces informations sont indispensables. Les modèles de distribution spatiale d'espèces sont donc devenus des moyens de décision importants. Les méthodes statistiques courantes comme les modèles linéaires généralisés (GLM) demandent des données de présence et d'absence des espèces. Cependant, souvent seules les données de présence sont disponibles, surtout pour les animaux migrants, rares ou cryptiques comme des papillons ou des reptiles. C'est pourquoi certains modélisateurs ont choisi des absences au hasard, avec le risque d'influencer le résultat en choisissant des fausses absences. Nous avons établi plusieurs stratégies, basées sur des données de distribution historique des papillons diurnes, pour sélectionner des absences plus fiables. Les résultats ont démontré que de meilleurs modèles pouvaient être obtenus lorsque les données proviennent des périodes de temps plus longues. En plus, la performance des modèles a pu être augmentée en considérant des données de distribution à long terme d'espèces qui occupent des habitats similaires à ceux de l'espèce cible. Vu le succès de cette stratégie, elle a été utilisée pour évaluer les effets potentiels des changements de paysage futurs sur la distribution des papillons des prairies sèches et marais, deux habitats qui ont souffert de graves détériorations. Quatre scénarios spatialement explicites, décrivant (i) l'extrapolation des changements de l'utilisation de sol tels qu'observés entre 1985 et 1997, (ii) la libéralisation des marchés agricoles, et une production agricole (iii) légèrement amoindrie et (iv) fortement diminuée, ont été utilisés pour générer des directions de changement probables. Les relations actuelles entre la distribution des espèces et l'environnement ont été déterminées par le biais des modèles statistiques et ont été utilisées pour calculer des probabilités de présence selon les scénarios dans six régions biogéographiques majeures de la Suisse, comportant le Jura, le Plateau, les Alpes du Nord, du Sud, centrales orientales et centrales occidentales. Les résultats principaux ont montré que les espèces des prairies sèches pourraient profiter d'une diminution de la production agricole, mais qu'elles pourraient aussi disparaître à cause de l'embroussaillement des terres ouvertes dû à la libéralisation des marchés agricoles. La probabilité de présence des espèces de marais a décrû à cause d'une perte générale des habitats favorables. De plus, les analyses ont confirmé que des causes humaines comme l'urbanisation, l'abandon des terres ouvertes et l'intensification de l'agriculture affectent actuellement ces espèces. Ainsi ces forces devraient être mieux prises en compte lors de planifications paysagères, pour que ces papillons diurnes puissent survivre dans leurs habitats actuels. Dans ce travail de thèse, des données historiques ont été intensivement utilisées pour reconstruire des développements anciens et pour les rendre utiles à des recherches contemporaines. Cependant, la disponibilité des données historiques et les analyses à grande échelle ont souvent limité le pouvoir explicatif des analyses. Des descripteurs pertinents pour caractériser les habitats anciens et des données suffisantes sur la distribution des espèces sont généralement rares, spécialement pour des analyses à des échelles fores. Cette situation peut être améliorée en augmentant l'étendue du site d'étude et la résolution, comme il a été fait dans cette thèse en considérant toute la Suisse avec ses communes. Cependant, les récents projets de surveillance et les techniques de collecte de données sont des sources prometteuses, qui pourraient permettre des analyses plus détaillés sur les réactions à long terme des espèces aux changements de paysage dans le futur. Ce travail a aussi montré la valeur des anciennes données de distribution, par exemple leur potentiel pour aider à localiser des' présences d'espèces encore inconnues. Les résultats peuvent contribuer à des activités de recherche à venir, qui étudieraient les distributions récentes ou futures d'espèces en considérant l'immense richesse des données de distribution historiques.