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

MIGCLIM: Predicting plant distribution and dispersal in a changing climate

Many studies have forecasted the possible impact of climate change on plant distribution using models based on ecological niche theory. In their basic implementation, niche-based models do not constrain predictions by dispersal limitations. Hence, most niche-based modelling studies published so far have assumed dispersal to be either unlimited or null. However, depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under- or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of "potentially suitable" and "potentially colonisable" habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed MIGCLIM, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. MIGCLIM implements various parameters, such as dispersal distance, increase in reproductive potential over time, barriers to dispersal or long distance dispersal. Several simulations were run for two virtual species in a study area of the western Swiss Alps, by varying dispersal distance and other parameters. Each simulation covered the hundred-year period 2001-2100 and three different IPCC-based temperature warming scenarios were considered. Our results indicate that: (i) using realistic parameter values, the future potential distributions generated using MIGCLIM can differ significantly (up to more than 95% decrease in colonized surface) from those that ignore dispersal; (ii) this divergence increases both with increasing climate warming and over longer time periods; (iii) the uncertainty associated with the warming scenario can be nearly as large as the one related to dispersal parameters; (iv) accounting for dispersal, even roughly, can importantly reduce uncertainty in projections.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Case studies and mathematical models of ecological speciation. 1. Cichlids in a crater lake.

A recent study of a pair of sympatric species of cichlids in Lake Apoyo in Nicaragua is viewed as providing probably one of the most convincing examples of sympatric speciation to date. Here, we describe and study a stochastic, individual-based, explicit genetic model tailored for this cichlid system. Our results show that relatively rapid (<20,000 generations) colonization of a new ecological niche and (sympatric or parapatric) speciation via local adaptation and divergence in habitat and mating preferences are theoretically plausible if: (i) the number of loci underlying the traits controlling local adaptation, and habitat and mating preferences is small; (ii) the strength of selection for local adaptation is intermediate; (iii) the carrying capacity of the population is intermediate; and (iv) the effects of the loci influencing nonrandom mating are strong. We discuss patterns and timescales of ecological speciation identified by our model, and we highlight important parameters and features that need to be studied empirically to provide information that can be used to improve the biological realism and power of mathematical models of ecological speciation.

Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non-native species

Aim Identifying climatic niche shifts and their drivers is important to accurately predict the risk of biological invasions. The niches of non-native plants and birds have recently been assessed in large-scale multi-species studies, but such large-scale tests are lacking for non-native reptiles and amphibians (herpetofauna). Furthermore, little is known about the factors contributing to niche shifts when they occur. Based on the occurrence of 71 reptile and amphibian species, we compared native and non-native realized niches in 101 invaded ranges at a worldwide scale and identified the factors that affect niche shifts. Location The world except the Antarctic. Methods We assessed climatic niche dynamics in a gridded environmental space allowing the quantification of niche overlap and expansion into climatic conditions not colonized by the species in their native range. We analyzed the factors affecting niche shifts using a model averaging approach based on generalized linear mixed-effects models. Results Approximately 57% of the invaded ranges (51% for amphibians and 61% for reptiles) showed niche shifts (≥10% expansion in the realized climatic niche). Island endemics, species introduced to Oceania and invaded ranges outside the native biogeographic realm showed a higher proportion of niche shifts. Niche shifts were more likely for species that had smaller native range sizes, were introduced earlier into a new range or invaded areas located at lower latitudes than the native range. Main conclusions The proportion of niche shifts for non-native herpetofauna was higher than those for Holarctic non-native plants and European non-native birds. The 'climate matching hypothesis' should be used with caution for species shifting their niche because it could underestimate the risk of their establishment.

An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data

1. Few examples of habitat-modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo-absences. 2. In this study we tested a new approach to generating pseudo-absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum. This method of generating pseudo-absences was compared with two others: (i) use of a GLM with pseudo-absences generated totally at random, and (ii) use of an ENFA only. 3. The influence of two different spatial resolutions (i.e. grain) was also assessed for tackling the dilemma of quality (grain) vs. quantity (number of occurrences). Each combination of the three above-mentioned methods with the two grains generated a distinct HS map. 4. Four evaluation measures were used for comparing these HS maps: total deviance explained, best kappa, Gini coefficient and minimal predicted area (MPA). The last is a new evaluation criterion proposed in this study. 5. Results showed that (i) GLM models using ENFA-weighted pseudo-absence provide better results, except for the MPA value, and that (ii) quality (spatial resolution and locational accuracy) of the data appears to be more important than quantity (number of occurrences). Furthermore, the proposed MPA value is suggested as a useful measure of model evaluation when used to complement classical statistical measures. 6. Synthesis and applications. We suggest that the use of ENFA-weighted pseudo-absence is a possible way to enhance the quality of GLM-based potential distribution maps and that data quality (i.e. spatial resolution) prevails over quantity (i.e. number of data). Increased accuracy of potential distribution maps could help to define better suitable areas for species protection and reintroduction.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Climate niche conservatism does not explain restricted distribution patterns in Tynanthus (Bignonieae, Bignoniaceae)

Studies on niche evolution allow us to establish how species niches have changed over time as well as to identify how long-term evolutionary processes have led to present-day species distributions. Here, we investigate the patterns of climatic niche evolution in Tynanthus (Bignonieae, Bignoniaceae), a genus comprising narrowly distributed species. We test the hypothesis that niche conservatism has played an important role in the diversification history of this group of Neotropical lianas. For that, we perform univariate and multivariate comparisons between species' climatic niches and associated environmental data with information on species' phylogenetic relationships. We encountered considerable divergence in niches among species, indicating that niche conservatism in climatic variables has does not seem to havenot played a key role in the diversification of the genus. Our results are used as a basis to discuss patterns of ecological niche evolution in the group and to suggest novel approaches for future analyses.

A macro-ecological perspective on crassulacean acid metabolism (CAM) photosynthesis evolution in Afro-Madagascan drylands: Eulophiinae orchids as a case study.

Crassulacean acid metabolism (CAM) photosynthesis is an adaptation to water and atmospheric CO2 deficits that has been linked to diversification in dry-adapted plants. We investigated whether CAM evolution can be associated with the availability of new or alternative niches, using Eulophiinae orchids as a case study. Carbon isotope ratios, geographical and climate data, fossil records and DNA sequences were used to: assess the prevalence of CAM in Eulophiinae orchids; characterize the ecological niche of extant taxa; infer divergence times; and estimate whether CAM is associated with niche shifts. CAM evolved in four terrestrial lineages during the late Miocene/Pliocene, which have uneven diversification patterns. These lineages originated in humid habitats and colonized dry/seasonally dry environments in Africa and Madagascar. Additional key features (variegation, heterophylly) evolved in the most species-rich CAM lineages. Dry habitats were also colonized by a lineage that includes putative mycoheterotrophic taxa. These findings indicate that the switch to CAM is associated with environmental change. With its suite of adaptive traits, this group of orchids represents a unique opportunity to study the adaptations to dry environments, especially in the face of projected global aridification.

Predicted decrease in global climate suitability masks regional complexity of invasive fruit fly species response to climate change

Climate change affects the rate of insect invasions as well as the abundance, distribution and impacts of such invasions on a global scale. Among the principal analytical approaches to predicting and understanding future impacts of biological invasions are Species Distribution Models (SDMs), typically in the form of correlative Ecological Niche Models (ENMs). An underlying assumption of ENMs is that species-environment relationships remain preserved during extrapolations in space and time, although this is widely criticised. The semi-mechanistic modelling platform, CLIMEX, employs a top-down approach using species ecophysiological traits and is able to avoid some of the issues of extrapolation, making it highly applicable to investigating biological invasions in the context of climate change. The tephritid fruit flies (Diptera: Tephritidae) comprise some of the most successful invasive species and serious economic pests around the world. Here we project 12 tephritid species CLIMEX models into future climate scenarios to examine overall patterns of climate suitability and forecast potential distributional changes for this group. We further compare the aggregate response of the group against species-specific responses. We then consider additional drivers of biological invasions to examine how invasion potential is influenced by climate, fruit production and trade indices. Considering the group of tephritid species examined here, climate change is predicted to decrease global climate suitability and to shift the cumulative distribution poleward. However, when examining species-level patterns, the predominant directionality of range shifts for 11 of the 12 species is eastward. Most notably, management will need to consider regional changes in fruit fly species invasion potential where high fruit production, trade indices and predicted distributions of these flies overlap.

Species delimitation: A case study in a problematic ant taxon

Species delimitation has been invigorated as a discipline in systematics by an influx of new character sets, analytical methods, and conceptual advances. We use genetic data from 68 markers, combined with distributional, bioclimatic, and coloration information, to hypothesize boundaries of evolutionarily independent lineages (species) within the widespread and highly variable nominal fire ant species Solenopsis saevissima, a member of a species group containing invasive pests as well as species that are models for ecological and evolutionary research. Our integrated approach uses diverse methods of analysis to sequentially test whether populations meet specific operational criteria (contingent properties) for candidacy as morphologically cryptic species, including genetic clustering, monophyly, reproductive isolation, and occupation of distinctive niche space. We hypothesize that nominal S. saevissima comprises at least 4-6 previously unrecognized species, including several pairs whose parapatric distributions implicate the development of intrinsic premating or postmating barriers to gene flow. Our genetic data further suggest that regional genetic differentiation in S. saevissima has been influenced by hybridization with other nominal species occurring in sympatry or parapatry, including the quite distantly related Solenopsis geminata. The results of this study illustrate the importance of employing different classes of genetic data (coding and noncoding regions and nuclear and mitochondrial DNA [mtDNA] markers), different methods of genetic data analysis (tree-based and non-tree based methods), and different sources of data (genetic, morphological, and ecological data) to explicitly test various operational criteria for species boundaries in clades of recently diverged lineages, while warning against over reliance on any single data type (e.g., mtDNA sequence variation) when drawing inferences.

Modelación de la distribución de especies y ecosistemas en el tiempo y en el espacio: una revisión de las nuevas herramientas y enfoques disponibles

This article aims to present the conceptual and methodological framework in which models techniques for species and ecosystems distribution are developed. An historical review of concepts behind these techniques is made as well as the presentation of the major methodological steps involved in these tests. A discussion on how these approaches are useful for the development of new questions in the field of biogeography and biological conservation is generated. Finally, an application of distribution modeling techniques, using the specie Beilschmiedia miersii (belloto Del Norte) as a study case, is presented. This conceptual and methodological review as well as the example applied, seeks to clarify the usefulness and potential of distribution models techniques, with the objective to go forward in biogeography research and thus, farther progress in understanding spatial and temporal patterns of organism's distribution

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Low dispersing species : population genetic processes in space and time : the genus "Trochulus" (Gastropoda: Hygromiidae) as a case study

RÉSUMÉ Une espèce est rarement composée d'une population unique. Parce que les individus ont des capacités de dispersion limitées et que les paysages sont des mosaïques d'habitats, la plupart des espèces sont plutôt composées de sous-populations connectées par la migration. Cette variation spatiale influence directement la distribution de la variabilité génétique dans et entre les populations. Durant ce travail, nous avons abordé certains des processus populationnels qui ont joué un rôle supposé dans l'apparition de nouvelles espèces au sein du genre Trochulus. Plus précisément, nous avons tenté d'évaluer les impacts respectifs de l'isolement passé (facteurs historiques) et présent (facteurs locaux). Nous avons d'abord pu montrer que les faibles capacités de dispersion des escargots terrestres ont directement influencé leur histoire évolutive à toutes les échelles spatiales et temporelles. En réduisant l'effet homogénéisant de la migration, une faible dispersion maintient dans les populations les traces génétiques d'évènements passés. A l'échelle de la distribution globale de Trochulus villosus, ces traces ont permis de reconstruire une histoire faite d'isolements et d'expansions de populations. En combinant des données génétiques avec une modélisation de la niche climatique passée, il a été possible de proposer un scénario significativement meilleur que toutes les hypothèses alternatives que nous avons testées. A l'échelle locale par contre, l'héritage historique est difficile à distinguer de la dynamique actuelle. Ce fut le cas des lignées mitochondriales du complexe sericeus-hispidus : les deux principales lignées étaient phylogénétiquement éloignées, avaient eu des démographies passées différentes et corrélaient avec des différences morphologiques. D'un autre côté, le flux de gène nucléaire était fort, contredisant l'idée de deux espèces cryptiques isolées reproductivement. Pour pouvoir conclure à la présence ou non de deux espèces, il nous a manqué des informations locales sur la dynamique des populations et les conditions écologiques que l'on trouve dans la région d'étude. Enfin, nous avons pu souligner que la connectivité entre populations d'escargots est soumise à la qualité des habitats et à leur organisation spatiale. Les escargots sont dépendants d'un habitat et s'y adaptent, comme l'indiquent la présence de «poils » uniquement sur la coquille d'espèces vivant dans des habitats humides ou la corrélation entre morphologie et habitat au sein du complexe sericeus-hispidus. Logiquement donc, les escargots migrent préférentiellement au travers d'habitats favorables comme l'a montré la réduction de flux de gènes au travers des prairies chez T. villosus (une espèce forestière). De ces données, nous pouvons supposer que les populations d'escargots en particulier, et des espèces à faible dispersion en général, ont de fortes chances d'être affectées par les changements climatiques, avec de probables implications pour leurs histoires évolutives. SUMMARY : Species rarely consists in a single population. Because individuals have limited dispersal abilities, because landscapes are habitat patchworks, most species are made of several subpopulations connected by migration. This spatial variation has consequences on the distribution of genetic diversity within and between populations, creating a structure among the populations. During the present work, we investigated some of the population processes assumed to have played an important role on the speciation within the genus Trochulus. More specifically, we questioned the respective impacts of past (historical factors) or present (local factors) population isolations. We first could show that the poor dispersal abilities of land snails have had profound impacts on their evolutionary histories at all spatial and temporal scales. Low dispersal maintains a strong signature of past events in the populations by minimising the homogenising effects of geneflow. At the scale of Trochulus villosus global distribution, they allowed to retrieve the detailed history of this species population isolations and expansions. Combining a large genetic dataset with paleo-climatic niche modelling ended up with a historical scenario significantly better than all traditional alternatives we tested. At local scale on the contrary, past events become difficult to tease apart from ongoing processes. This was the case for the divergent mitochondria) lineages within the sericeus-hispidus complex: the two principal lineages appeared to be phylogenetically distant, to have experienced different demographic histories and to correlate with morphological differences. On the other hand, nuclear (present day) geneflow was high, contradicting the idea of two reproductively isolated cryptic species. Information on the local population dynamics and environmental conditions are lacking to be able to decide whether past isolation has indeed resulted here in new species. Finally, we emphasised the importance of the habitat types present in a landscape as well as their spatial organisation for the population connectivity of land snails. These species are tightly dependent on a habitat and adapt to it as shown by thé occurrence of hair-like structures only in species living in humid environments or by the correlation between shell morphology and habitat in the sericeus-hispidus complex. As a result, land snails preferentially migrate through favourable habitats: Trochulus villosus, a forest species, had its geneflow significantly reduced across meadows. From these data, we can hypothesise that the populations of land snails in particular and of low dispersing species in general are likely to be strongly affected by the ongoing climate changes, with potential major consequences on their evolutionary histories.

Effects of phylogenetic signal on ancestral state reconstruction.

One of the standard tools used to understand the processes shaping trait evolution along the branches of a phylogenetic tree is the reconstruction of ancestral states (Pagel 1999). The purpose is to estimate the values of the trait of interest for every internal node of a phylogenetic tree based on the trait values of the extant species, a topology and, depending on the method used, branch lengths and a model of trait evolution (Ronquist 2004). This approach has been used in a variety of contexts such as biogeography (e.g., Nepokroeff et al. 2003, Blackburn 2008), ecological niche evolution (e.g., Smith and Beaulieu 2009, Evans et al. 2009) and metabolic pathway evolution (e.g., Gabaldón 2003, Christin et al. 2008). Investigations of the factors affecting the accuracy with which ancestral character states can be reconstructed have focused in particular on the choice of statistical framework (Ekman et al. 2008) and the selection of the best model of evolution (Cunningham et al. 1998, Mooers et al. 1999). However, other potential biases affecting these methods, such as the effect of tree shape (Mooers 2004), taxon sampling (Salisbury and Kim 2001) as well as reconstructing traits involved in species diversification (Goldberg and Igić 2008), have also received specific attention. Most of these studies conclude that ancestral character states reconstruction is still not perfect, and that further developments are necessary to improve its accuracy (e.g., Christin et al. 2010). Here, we examine how different estimations of branch lengths affect the accuracy of ancestral character state reconstruction. In particular, we tested the effect of using time-calibrated versus molecular branch lengths and provide guidelines to select the most appropriate branch lengths to reconstruct the ancestral state of a trait.