Predicting species distributions for conservation decisions.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Movement, impacts and management of plant distributions in response to climate change: insights from invasions

A major challenge in this era of rapid climate change is to predict changes in species distributions and their impacts on ecosystems, and, if necessary, to recommend management strategies for maintenance of biodiversity or ecosystem services. Biological invasions, studied in most biomes of the world, can provide useful analogs for some of the ecological consequences of species distribution shifts in response to climate change. Invasions illustrate the adaptive and interactive responses that can occur when species are confronted with new environmental conditions. Invasion ecology complements climate change research and provides insights into the following questions: i) how will species distributions respond to climate change? ii) how will species movement affect recipient ecosystems? and iii) should we, and if so how can we, manage species and ecosystems in the face of climate change? Invasion ecology demonstrates that a trait-based approach can help to predict spread speeds and impacts on ecosystems, and has the potential to predict climate change impacts on species ranges and recipient ecosystems. However, there is a need to analyse traits in the context of life-history and demography, the stage in the colonisation process (e.g., spread, establishment or impact), the distribution of suitable habitats in the landscape, and the novel abiotic and biotic conditions under which those traits are expressed. As is the case with climate change, invasion ecology is embedded within complex societal goals. Both disciplines converge on similar questions of "when to intervene?" and "what to do?" which call for a better understanding of the ecological processes and social values associated with changing ecosystems.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large-scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (similar to 9%) compared to the contribution of each predictor set individually (similar to 20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo-climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.

Heterogeneous 40Ar* distributions in naturally deformed muscovite: in situ UV-laser ablation evidence for micro structurally controlled intragrain diffusion

Micas are commonly used in Ar-40/Ar-39 thermochronological studies of variably deformed rocks yet the physical basis by which deformation may affect radiogenic argon retention in mica is poorly constrained. This study examines the relationship between deformation and deformation-induced microstructures on radiogenic argon retention in muscovite, A combination of furnace step-heating and high-spatial resolution in situ UV-laser ablation Ar-40/Ar-39 analyses are reported for deformed muscovites sampled from a granitic pegmatite vein within the Siviez-Mischabel Nappe, western Swiss Alps (Penninic domain, Brianconnais unit). The pegmatite forms part of the Variscan (similar to 350 Ma) Alpine basement and exhibits a prominent Alpine S-C fabric including numerous mica `fish' that developed under greenschist facies metamorphic conditions, during the dominant Tertiary Alpine tectonic phase of nappe emplacement. Furnace step-heating of milligram quantities of separated muscovite grains yields an Ar-40/Ar-39 age spectrum with two distinct staircase segments but without any statistical plateau, consistent with a previous study from the same area. A single (3 X 5 mm) muscovite porphyroclast (fish) was investigated by in situ UV-laser ablation. A histogram plot of 170 individual Ar-40/Ar-39 UV-laser ablation ages exhibit a range from 115 to 387 Ma with modes at approximately 340 and 260 Ma. A variogram statistical treatment of the (40)Ad/Ar-39 results reveals ages correlated with two directions; a highly correlated direction at 310 degrees and a lesser correlation at 0 degrees relative to the sense of shearing. Using the highly correlated direction a statistically generated (Kriging method) age contour map of the Ar-40/Ar-39 data reveals a series of elongated contours subparallel to the C-surfaces which where formed during Tertiary nappe emplacement. Similar data distributions and slightly younger apparent ages are recognized in a smaller mica fish. The observed intragrain age variations are interpreted to reflect the partial loss of radiogenic argon during Alpine (similar to 35 Ma) greenschist facies metamorphism. One-dirnensional diffusion modelling results are consistent with the idea that the zones of youngest apparent age represent incipient shear band development within the mica porphyroclasts, thus providing a network of fast diffusion pathways. During Alpine greenschist facies metamorphism the incipient shear bands enhanced the intragrain loss of radiogenic argon. The structurally controlled intragrain age variations observed in this investigation imply that deformation has a direct control on the effective length scale for argon diffusion, which is consistent with the heterogeneous nature of deformation. (C) 2001 Elsevier Science B.V. All rights reserved.

BIOMOD - a platform for ensemble forecasting of species distributions

BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

The role of phylogeny in the spatial distributions and assembly of mountain plant communities.

A major challenge in community ecology is a thorough understanding of the processes that govern the assembly and composition of communities in time and space. The growing threat of climate change to the vascular plant biodiversity of fragile ecosystems such as mountains has made it equally imperative to develop comprehensive methodologies to provide insights into how communities are assembled. In this perspective, the primary objective of this PhD thesis is to contribute to the theoretical and methodological development of community ecology, by proposing new solutions to better detect the ecological and evolutionary processes that govern community assembly. As phylogenetic trees provide by far, the most advanced tools to integrate the spatial, ecological and evolutionary dynamics of plant communities, they represent the cornerstone on which this work was based. In this thesis, I proposed new solutions to: (i) reveal trends in community assembly on phylogenies, depicted by the transition of signals at the nodes of the different species and lineages responsible for community assembly, (ii) contribute to evidence the importance of evolutionarily labile traits in the distribution of mountain plant species. More precisely, I demonstrated that phylogenetic and functional compositional turnover in plant communities was driven by climate and human land use gradients mostly influenced by evolutionarily labile traits, (iii) predict and spatially project the phylogenetic structure of communities using species distribution models, to identify the potential distribution of phylogenetic diversity, as well as areas of high evolutionary potential along elevation. The altitudinal setting of the Diablerets mountains (Switzerland) provided an appropriate model for this study. The elevation gradient served as a compression of large latitudinal variations similar to a collection of islands within a single area, and allowed investigations on a large number of plant communities. Overall, this thesis highlights that stochastic and deterministic environmental filtering processes mainly influence the phylogenetic structure of plant communities in mountainous areas. Negative density-dependent processes implied through patterns of phylogenetic overdispersion were only detected at the local scale, whereas environmental filtering implied through phylogenetic clustering was observed at both the regional and local scale. Finally, the integration of indices of phylogenetic community ecology with species distribution models revealed the prospects of providing novel and insightful explanations on the potential distribution of phylogenetic biodiversity in high mountain areas. These results generally demonstrate the usefulness of phylogenies in inferring assembly processes, and are worth considering in the theoretical and methodological development of tools to better understand phylogenetic community structure.

Quantitative analysis of crystal/grain sizes and their distributions in 2D and 3D

We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.

Cross-amplification of polymorphic microsatellites reveals extra-pair paternity and brood parasitism in Sturnus vulgaris

We tested the cross-amplification of 37 microsatellites in a population of starlings (Stumus vulgaris). Twenty-three of them amplified and five exhibited a large number of alleles per locus and high heterozygosity (on average: 14.6 alleles/locus and H. = 0.704). We assessed the occurrence of extra-pair paternity (EPP) and intraspecific brood parasitism GBP) in this population. The EPP rate was 16% to 18% offspring from 43% to 45% of nests. IBP was very variable between two successive years (14% to 27% chicks from 25% to 64% of clutches). These five polymorphic markers will be of potential use in studies of genetic diversity, population structure and reproductive strategy of this species.

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

Extra-pair paternity, testes size and testosterone level in relation to colour polymorphism in the barn owl Tyto alba

In many bird populations, individuals display one of several genetically inherited colour morphs. Colour polymorphism can be maintained by several mechanisms one of which being frequency-dependent selection with colour morphs signalling alternative mating strategies. One morph may be dominant and territorial, and another one adopt a sneaky behaviour to gain access to fertile females. We tested this hypothesis in the barn owl Tyto alba in which coloration varies from reddish-brown to white. This trait is heritable and neither sensitive to the environment in which individuals live nor to body condition. In Switzerland, reddish-brown males were observed to feed their brood at a higher rate and to produce more offspring than white males. This observation lead us to hypothesize that white males may equalise fitness by investing more effort in extra-pair copulations. This hypothesis predicts that lighter Coloured males produce more extra-pair young, have larger testes and higher levels of circulating testosterone. However, our results are not consistent with these three predictions. First, paternity analyses of 54 broods with a total of 211 offspring revealed that only one young was not sired by the male that was feeding it. Second, testes size was not correlated with male plumage coloration suggesting that white males are not sexually more active. Finally, in nestlings at the time of feather growth testosterone level was not related to plumage coloration suggesting that this androgen is not required for the expression of this plumage trait. Our study therefore indicates that in the barn owl colour polymorphism plays no role in the probability of producing extra-pair young.

Cheminformatic studies of molecular properties and their influence on bioactivity in the context of drug discovery

Molecular shape has long been known to be an important property for the process of molecular recognition. Previous studies postulated the existence of a drug-like shape space that could be used to artificially bias the composition of screening libraries, with the aim to increase the chance of success in Hit Identification. In this work, it was analysed to which extend this assumption holds true. Normalized Principal Moments of Inertia Ratios (NPRs) have been used to describe the molecular shape of small molecules. It was investigated, whether active molecules of diverse targets are located in preferred subspaces of the NPR shape space. Results illustrated a significantly stronger clustering than could be expected by chance, with parts of the space unlikely to be occupied by active compounds. Furthermore, a strong enrichment of elongated, rather flat shapes could be observed, while globular compounds were highly underrepresented. This was confirmed for a wide range of small molecule datasets from different origins. Active compounds exhibited a high overlap in their shape distributions across different targets, making a purely shape­ based discrimination very difficult. An additional perspective was provided by comparing the shapes of protein binding pockets with those of their respective ligands. Although more globular than their ligands, it was observed that binding sites shapes exhibited a similarly skewed distribution in shape space: spherical shapes were highly underrepresented. This was different for unoccupied binding pockets of smaller size. These were on the contrary identified to possess a more globular shape. The relation between shape complementarity and exhibited bioactivity was analysed; a moderate correlation between bioactivity and parameters including pocket coverage, distance in shape space, and others could be identified, which reflects the importance of shape complementarity. However, this also suggests that other aspects are of relevance for molecular recognition. A subsequent analysis assessed if and how shape and volume information retrieved from pocket or respective reference ligands could be used as a pre-filter in a virtual screening approach. ln Lead Optimization compounds need to get optimized with respect to a variety of pararneters. Here, the availability of past success stories is very valuable, as they can guide medicinal chemists during their analogue synthesis plans. However, although of tremendous interest for the public domain, so far only large corporations had the ability to mine historical knowledge in their proprietary databases. With the aim to provide such information, the SwissBioisostere database was developed and released during this thesis. This database contains information on 21,293,355 performed substructural exchanges, corresponding to 5,586,462 unique replacements that have been measured in 35,039 assays against 1,948 molecular targets representing 30 target classes, and on their impact on bioactivity . A user-friendly interface was developed that provides facile access to these data and is accessible at http//www.swissbioisostere.ch. The ChEMBL database was used as primary data source of bioactivity information. Matched molecular pairs have been identified in the extracted and cleaned data. Success-based scores were developed and integrated into the database to allow re-ranking of proposed replacements by their past outcomes. It was analysed to which degree these scores correlate with chemical similarity of the underlying fragments. An unexpectedly weak relationship was detected and further investigated. Use cases of this database were envisioned, and functionalities implemented accordingly: replacement outcomes are aggregatable at the assay level, and it was shawn that an aggregation at the target or target class level could also be performed, but should be accompanied by a careful case-by-case assessment. It was furthermore observed that replacement success depends on the activity of the starting compound A within a matched molecular pair A-B. With increasing potency the probability to lose bioactivity through any substructural exchange was significantly higher than in low affine binders. A potential existence of a publication bias could be refuted. Furthermore, often performed medicinal chemistry strategies for structure-activity-relationship exploration were analysed using the acquired data. Finally, data originating from pharmaceutical companies were compared with those reported in the literature. It could be seen that industrial medicinal chemistry can access replacement information not available in the public domain. In contrast, a large amount of often-performed replacements within companies could also be identified in literature data. Preferences for particular replacements differed between these two sources. The value of combining different endpoints in an evaluation of molecular replacements was investigated. The performed studies highlighted furthermore that there seem to exist no universal substructural replacement that always retains bioactivity irrespective of the biological environment. A generalization of bioisosteric replacements seems therefore not possible. - La forme tridimensionnelle des molécules a depuis longtemps été reconnue comme une propriété importante pour le processus de reconnaissance moléculaire. Des études antérieures ont postulé que les médicaments occupent préférentiellement un sous-ensemble de l'espace des formes des molécules. Ce sous-ensemble pourrait être utilisé pour biaiser la composition de chimiothèques à cribler, dans le but d'augmenter les chances d'identifier des Hits. L'analyse et la validation de cette assertion fait l'objet de cette première partie. Les Ratios de Moments Principaux d'Inertie Normalisés (RPN) ont été utilisés pour décrire la forme tridimensionnelle de petites molécules de type médicament. Il a été étudié si les molécules actives sur des cibles différentes se co-localisaient dans des sous-espaces privilégiés de l'espace des formes. Les résultats montrent des regroupements de molécules incompatibles avec une répartition aléatoire, avec certaines parties de l'espace peu susceptibles d'être occupées par des composés actifs. Par ailleurs, un fort enrichissement en formes allongées et plutôt plates a pu être observé, tandis que les composés globulaires étaient fortement sous-représentés. Cela a été confirmé pour un large ensemble de compilations de molécules d'origines différentes. Les distributions de forme des molécules actives sur des cibles différentes se recoupent largement, rendant une discrimination fondée uniquement sur la forme très difficile. Une perspective supplémentaire a été ajoutée par la comparaison des formes des ligands avec celles de leurs sites de liaison (poches) dans leurs protéines respectives. Bien que plus globulaires que leurs ligands, il a été observé que les formes des poches présentent une distribution dans l'espace des formes avec le même type d'asymétrie que celle observée pour les ligands: les formes sphériques sont fortement sous­ représentées. Un résultat différent a été obtenu pour les poches de plus petite taille et cristallisées sans ligand: elles possédaient une forme plus globulaire. La relation entre complémentarité de forme et bioactivité a été également analysée; une corrélation modérée entre bioactivité et des paramètres tels que remplissage de poche, distance dans l'espace des formes, ainsi que d'autres, a pu être identifiée. Ceci reflète l'importance de la complémentarité des formes, mais aussi l'implication d'autres facteurs. Une analyse ultérieure a évalué si et comment la forme et le volume d'une poche ou de ses ligands de référence pouvaient être utilisés comme un pré-filtre dans une approche de criblage virtuel. Durant l'optimisation d'un Lead, de nombreux paramètres doivent être optimisés simultanément. Dans ce contexte, la disponibilité d'exemples d'optimisations réussies est précieuse, car ils peuvent orienter les chimistes médicinaux dans leurs plans de synthèse par analogie. Cependant, bien que d'un extrême intérêt pour les chercheurs dans le domaine public, seules les grandes sociétés pharmaceutiques avaient jusqu'à présent la capacité d'exploiter de telles connaissances au sein de leurs bases de données internes. Dans le but de remédier à cette limitation, la base de données SwissBioisostere a été élaborée et publiée dans le domaine public au cours de cette thèse. Cette base de données contient des informations sur 21 293 355 échanges sous-structuraux observés, correspondant à 5 586 462 remplacements uniques mesurés dans 35 039 tests contre 1948 cibles représentant 30 familles, ainsi que sur leur impact sur la bioactivité. Une interface a été développée pour permettre un accès facile à ces données, accessible à http:/ /www.swissbioisostere.ch. La base de données ChEMBL a été utilisée comme source de données de bioactivité. Une version modifiée de l'algorithme de Hussain et Rea a été implémentée pour identifier les Matched Molecular Pairs (MMP) dans les données préparées au préalable. Des scores de succès ont été développés et intégrés dans la base de données pour permettre un reclassement des remplacements proposés selon leurs résultats précédemment observés. La corrélation entre ces scores et la similarité chimique des fragments correspondants a été étudiée. Une corrélation plus faible qu'attendue a été détectée et analysée. Différents cas d'utilisation de cette base de données ont été envisagés, et les fonctionnalités correspondantes implémentées: l'agrégation des résultats de remplacement est effectuée au niveau de chaque test, et il a été montré qu'elle pourrait également être effectuée au niveau de la cible ou de la classe de cible, sous réserve d'une analyse au cas par cas. Il a en outre été constaté que le succès d'un remplacement dépend de l'activité du composé A au sein d'une paire A-B. Il a été montré que la probabilité de perdre la bioactivité à la suite d'un remplacement moléculaire quelconque est plus importante au sein des molécules les plus actives que chez les molécules de plus faible activité. L'existence potentielle d'un biais lié au processus de publication par articles a pu être réfutée. En outre, les stratégies fréquentes de chimie médicinale pour l'exploration des relations structure-activité ont été analysées à l'aide des données acquises. Enfin, les données provenant des compagnies pharmaceutiques ont été comparées à celles reportées dans la littérature. Il a pu être constaté que les chimistes médicinaux dans l'industrie peuvent accéder à des remplacements qui ne sont pas disponibles dans le domaine public. Par contre, un grand nombre de remplacements fréquemment observés dans les données de l'industrie ont également pu être identifiés dans les données de la littérature. Les préférences pour certains remplacements particuliers diffèrent entre ces deux sources. L'intérêt d'évaluer les remplacements moléculaires simultanément selon plusieurs paramètres (bioactivité et stabilité métabolique par ex.) a aussi été étudié. Les études réalisées ont souligné qu'il semble n'exister aucun remplacement sous-structural universel qui conserve toujours la bioactivité quel que soit le contexte biologique. Une généralisation des remplacements bioisostériques ne semble donc pas possible.

Plant species distributions along environmental gradients: do belowground interactions with fungi matter?

The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of biotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs) on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models (SDMs), we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.