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.

The future of terrestrial mammals in the Mediterranean basin under climate change.

The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Modelling climate impact on floods with ensemble climate projections

The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 ‘ENSEMBLES’ project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble. The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding. Copyright © 2012 Royal Meteorological Society

Combining palaeodistribution modelling and phylogeographical approaches for identifying glacial refugia in Alpine Primula

Aim We investigated the late Quaternary history of two closely related and partly sympatric species of Primula from the south-western European Alps, P. latifolia Lapeyr. and P. marginata Curtis, by combining phylogeographical and palaeodistribution modelling approaches. In particular, we were interested in whether the two approaches were congruent and identified the same glacial refugia. Location South-western European Alps. Methods For the phylogeographical analysis we included 353 individuals from 28 populations of P. marginata and 172 individuals from 15 populations of P. latifolia and used amplified fragment length polymorphisms (AFLPs). For palaeodistribution modelling, species distribution models (SDMs) were based on extant species occurrences and then projected to climate models (CCSM, MIROC) of the Last Glacial Maximum (LGM), approximately 21 ka. Results The locations of the modelled LGM refugia were confirmed by various indices of genetic variation. The refugia of the two species were largely geographically isolated, overlapping only 6% to 11% of the species' total LGM distribution. This overlap decreased when the position of the glacial ice sheet and the differential elevational and edaphic distributions of the two species were considered. Main conclusions The combination of phylogeography and palaeodistribution modelling proved useful in locating putative glacial refugia of two alpine species of Primula. The phylogeographical data allowed us to identify those parts of the modelled LGM refugial area that were likely source areas for recolonization. The use of SDMs predicted LGM refugial areas substantially larger and geographically more divergent than could have been predicted by phylogeographical data alone

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.

GIS and geodatabases application to global scale plate tectonics modelling

Les reconstructions palinspastiques fournissent le cadre idéal à de nombreuses études géologiques, géographiques, océanographique ou climatiques. En tant qu?historiens de la terre, les "reconstructeurs" essayent d?en déchiffrer le passé. Depuis qu?ils savent que les continents bougent, les géologues essayent de retracer leur évolution à travers les âges. Si l?idée originale de Wegener était révolutionnaire au début du siècle passé, nous savons depuis le début des années « soixante » que les continents ne "dérivent" pas sans but au milieu des océans mais sont inclus dans un sur-ensemble associant croûte « continentale » et « océanique »: les plaques tectoniques. Malheureusement, pour des raisons historiques aussi bien que techniques, cette idée ne reçoit toujours pas l'écho suffisant parmi la communauté des reconstructeurs. Néanmoins, nous sommes intimement convaincus qu?en appliquant certaines méthodes et certains principes il est possible d?échapper à l?approche "Wégenerienne" traditionnelle pour enfin tendre vers la tectonique des plaques. Le but principal du présent travail est d?exposer, avec tous les détails nécessaires, nos outils et méthodes. Partant des données paléomagnétiques et paléogéographiques classiquement utilisées pour les reconstructions, nous avons développé une nouvelle méthodologie replaçant les plaques tectoniques et leur cinématique au coeur du problème. En utilisant des assemblages continentaux (aussi appelés "assemblées clés") comme des points d?ancrage répartis sur toute la durée de notre étude (allant de l?Eocène jusqu?au Cambrien), nous développons des scénarios géodynamiques permettant de passer de l?une à l?autre en allant du passé vers le présent. Entre deux étapes, les plaques lithosphériques sont peu à peu reconstruites en additionnant/ supprimant les matériels océaniques (symbolisés par des isochrones synthétiques) aux continents. Excepté lors des collisions, les plaques sont bougées comme des entités propres et rigides. A travers les âges, les seuls éléments évoluant sont les limites de plaques. Elles sont préservées aux cours du temps et suivent une évolution géodynamique consistante tout en formant toujours un réseau interconnecté à travers l?espace. Cette approche appelée "limites de plaques dynamiques" intègre de multiples facteurs parmi lesquels la flottabilité des plaques, les taux d'accrétions aux rides, les courbes de subsidence, les données stratigraphiques et paléobiogéographiques aussi bien que les évènements tectoniques et magmatiques majeurs. Cette méthode offre ainsi un bon contrôle sur la cinématique des plaques et fournit de sévères contraintes au modèle. Cette approche "multi-source" nécessite une organisation et une gestion des données efficaces. Avant le début de cette étude, les masses de données nécessaires était devenues un obstacle difficilement surmontable. Les SIG (Systèmes d?Information Géographiques) et les géo-databases sont des outils informatiques spécialement dédiés à la gestion, au stockage et à l?analyse des données spatialement référencées et de leurs attributs. Grâce au développement dans ArcGIS de la base de données PaleoDyn nous avons pu convertir cette masse de données discontinues en informations géodynamiques précieuses et facilement accessibles pour la création des reconstructions. Dans le même temps, grâce à des outils spécialement développés, nous avons, tout à la fois, facilité le travail de reconstruction (tâches automatisées) et amélioré le modèle en développant fortement le contrôle cinématique par la création de modèles de vitesses des plaques. Sur la base des 340 terranes nouvellement définis, nous avons ainsi développé un set de 35 reconstructions auxquelles est toujours associé un modèle de vitesse. Grâce à cet ensemble de données unique, nous pouvons maintenant aborder des problématiques majeurs de la géologie moderne telles que l?étude des variations du niveau marin et des changements climatiques. Nous avons commencé par aborder un autre problème majeur (et non définitivement élucidé!) de la tectonique moderne: les mécanismes contrôlant les mouvements des plaques. Nous avons pu observer que, tout au long de l?histoire de la terre, les pôles de rotation des plaques (décrivant les mouvements des plaques à la surface de la terre) tendent à se répartir le long d'une bande allant du Pacifique Nord au Nord de l'Amérique du Sud, l'Atlantique Central, l'Afrique du Nord, l'Asie Centrale jusqu'au Japon. Fondamentalement, cette répartition signifie que les plaques ont tendance à fuir ce plan médian. En l'absence d'un biais méthodologique que nous n'aurions pas identifié, nous avons interprété ce phénomène comme reflétant l'influence séculaire de la Lune sur le mouvement des plaques. La Lune sur le mouvement des plaques. Le domaine océanique est la clé de voute de notre modèle. Nous avons attaché un intérêt tout particulier à le reconstruire avec beaucoup de détails. Dans ce modèle, la croûte océanique est préservée d?une reconstruction à l?autre. Le matériel crustal y est symbolisé sous la forme d?isochrones synthétiques dont nous connaissons les âges. Nous avons également reconstruit les marges (actives ou passives), les rides médio-océaniques et les subductions intra-océaniques. En utilisant ce set de données très détaillé, nous avons pu développer des modèles bathymétriques 3-D unique offrant une précision bien supérieure aux précédents.<br/><br/>Palinspastic reconstructions offer an ideal framework for geological, geographical, oceanographic and climatology studies. As historians of the Earth, "reconstructers" try to decipher the past. Since they know that continents are moving, geologists a trying to retrieve the continents distributions through ages. If Wegener?s view of continent motions was revolutionary at the beginning of the 20th century, we know, since the Early 1960?s that continents are not drifting without goal in the oceanic realm but are included in a larger set including, all at once, the oceanic and the continental crust: the tectonic plates. Unfortunately, mainly due to technical and historical issues, this idea seems not to receive a sufficient echo among our particularly concerned community. However, we are intimately convinced that, by applying specific methods and principles we can escape the traditional "Wegenerian" point of view to, at last, reach real plate tectonics. This is the main aim of this study to defend this point of view by exposing, with all necessary details, our methods and tools. Starting with the paleomagnetic and paleogeographic data classically used in reconstruction studies, we developed a modern methodology placing the plates and their kinematics at the centre of the issue. Using assemblies of continents (referred as "key assemblies") as anchors distributed all along the scope of our study (ranging from Eocene time to Cambrian time) we develop geodynamic scenarios leading from one to the next, from the past to the present. In between, lithospheric plates are progressively reconstructed by adding/removing oceanic material (symbolized by synthetic isochrones) to major continents. Except during collisions, plates are moved as single rigid entities. The only evolving elements are the plate boundaries which are preserved and follow a consistent geodynamical evolution through time and form an interconnected network through space. This "dynamic plate boundaries" approach integrates plate buoyancy factors, oceans spreading rates, subsidence patterns, stratigraphic and paleobiogeographic data, as well as major tectonic and magmatic events. It offers a good control on plate kinematics and provides severe constraints for the model. This multi-sources approach requires an efficient data management. Prior to this study, the critical mass of necessary data became a sorely surmountable obstacle. GIS and geodatabases are modern informatics tools of specifically devoted to store, analyze and manage data and associated attributes spatially referenced on the Earth. By developing the PaleoDyn database in ArcGIS software we converted the mass of scattered data offered by the geological records into valuable geodynamical information easily accessible for reconstructions creation. In the same time, by programming specific tools we, all at once, facilitated the reconstruction work (tasks automation) and enhanced the model (by highly increasing the kinematic control of plate motions thanks to plate velocity models). Based on the 340 terranes properly defined, we developed a revised set of 35 reconstructions associated to their own velocity models. Using this unique dataset we are now able to tackle major issues of the geology (such as the global sea-level variations and climate changes). We started by studying one of the major unsolved issues of the modern plate tectonics: the driving mechanism of plate motions. We observed that, all along the Earth?s history, plates rotation poles (describing plate motions across the Earth?s surface) tend to follow a slight linear distribution along a band going from the Northern Pacific through Northern South-America, Central Atlantic, Northern Africa, Central Asia up to Japan. Basically, it sighifies that plates tend to escape this median plan. In the absence of a non-identified methodological bias, we interpreted it as the potential secular influence ot the Moon on plate motions. The oceanic realms are the cornerstone of our model and we attached a particular interest to reconstruct them with many details. In this model, the oceanic crust is preserved from one reconstruction to the next. The crustal material is symbolised by the synthetic isochrons from which we know the ages. We also reconstruct the margins (active or passive), ridges and intra-oceanic subductions. Using this detailed oceanic dataset, we developed unique 3-D bathymetric models offering a better precision than all the previously existing ones.

Fire management, climate change and their interacting effects on birds in complex Mediterranean landscapes: dynamic distribution modelling of an early-successional species - the near-threatened Dartford Warbler (Sylvia undata)

The current challenge in a context of major environmental changes is to anticipate the responses of species to future landscape and climate scenarios. In the Mediterranean basin, climate change is one the most powerful driving forces of fire dynamics, with fire frequency and impact having markedly increased in recent years. Species distribution modelling plays a fundamental role in this challenge, but better integration of available ecological knowledge is needed to adequately guide conservation efforts. Here, we quantified changes in habitat suitability of an early-succession bird in Catalonia, the Dartford Warbler (Sylvia undata) ― globally evaluated as Near Threatened in the IUCN Red List. We assessed potential changes in species distributions between 2000 and 2050 under different fire management and climate change scenarios and described landscape dynamics using a spatially-explicit fire-succession model that simulates fire impacts in the landscape and post-fire regeneration (MEDFIRE model). Dartford Warbler occurrence data were acquired at two different spatial scales from: 1) the Atlas of European Breeding Birds (EBCC) and 2) Catalan Breeding Bird Atlas (CBBA). Habitat suitability was modelled using five widely-used modelling techniques in an ensemble forecasting framework. Our results indicated considerable habitat suitability losses (ranging between 47% and 57% in baseline scenarios), which were modulated to a large extent by fire regime changes derived from fire management policies and climate changes. Such result highlighted the need for taking the spatial interaction between climate changes, fire-mediated landscape dynamics and fire management policies into account for coherently anticipating habitat suitability changes of early succession bird species. We conclude that fire management programs need to be integrated into conservation plans to effectively preserve sparsely forested and early succession habitats and their associated species in the face of global environmental change.

Overcoming limitations of modelling rare species by using ensembles of small models

1. Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. 2. For each species numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These 'ensembles of small models' (ESMs) were compared to standard Species Distribution Models (SDMs) using three commonly used modelling techniques (GLM, GBM, Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. 3. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were independently evaluated using a transferability assessment. 4. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.