Unravelling plant diversification: Intraspecific genetic differentiation in hybridizing Anacyclus species in the western Mediterranean Basin.

PREMISE: The interfertile species Anacyclus clavatus, A. homogamos, and A. valentinus represent a plant complex coexisting in large anthropic areas of the western Mediterranean Basin with phenotypically mixed populations exhibiting a great floral variation. The goal of this study was to estimate the genetic identity of each species, to infer the role of hybridization in the observed phenotypic diversity, and to explore the effect of climate on the geographic distribution of species and genetic clusters. METHODS: We used eight nuclear microsatellites to genotype 585 individuals from 31 populations of three Anacyclus species for population genetic analyses by using clustering algorithms based on Bayesian models and ordination methods. In addition, we used ecological niche models and niche overlap analyses for both the species and genetic clusters. We used an expanded data set, including 721 individuals from 129 populations for ecological niche models of the genetic clusters. RESULTS: We found a clear correspondence between species and genetic clusters, except for A. clavatus that included up to three genetic clusters. We detected individuals with admixed genetic ancestry in A. clavatus and in mixed populations. Ecological niche models predicted similar distributions for species and genetic clusters. For the two specific genetic clusters of A. clavatus, ecological niche models predicted remarkably different areas. CONCLUSIONS: Gene flow between Anacyclus species likely explains phenotypic diversity in contact areas. In addition, we suggest that introgression could be involved in the origin of one of the two A. clavatus genetic clusters, which also showed ecological differentiation.

Forecast increase in invasive rabbit spread into ecosystems of an oceanic island (Tenerife) under climate change.

The European rabbit (Oryctolagus cuniculus) is a pest and a conservation problem on many islands, where its heavy grazing pressure threatens many endemic plants with extinction. Previous studies in its native and introduced range have highlighted the high spatial variability of rabbit abundance at local and landscape scales, depending on many factors such as the existence of different habitats. Modeling of the species can be useful to better understand spatial patterns and to prioritize actions, especially in those regions in which rabbits have become invasive. Here, we investigate the distribution of the European rabbit in Tenerife (Canary Islands, Spain), where the species was introduced during the 15th century and has subsequently changed vegetation composition. Added to the direct effects of rabbits on vegetation, climate change could also have implications for rabbit populations, especially in the alpine ecosystem. To evaluate that, we estimated rabbit abundance in 216 plots randomly distributed on Tenerife island (61 in the alpine ecosystem), modeled the potential current spatial abundance of the species and considered how it might vary under different climate change scenarios. We associated rabbit abundance to a wide selection of abiotic, biotic, and human variables expected to influence rabbit abundance on the island. We found a positive correlation between rabbit abundance and temperature and a negative correlation in the case of precipitation. Hence, according to the models' projections, climate change is expected to enhance rabbit populations in the future. Current higher densities were related to land disturbance and open areas, and a remarkable increase is expected to occur in the alpine ecosystem. Overall, we consider that this study provides valuable information for land managers in the Canary archipelago as it reveals how global warming could indirectly exacerbate the conservation problems of the endemic flora in oceanic islands.

Genetic consequences of Quaternary climatic oscillations in the Himalayas: Primula tibetica as a case study based on restriction site-associated DNA sequencing.

The effects of Quaternary climatic oscillations on the demography of organisms vary across regions and continents. In taxa distributed in Europe and North America, several paradigms regarding the distribution of refugia have been identified. By contrast, less is known about the processes that shaped the species' spatial genetic structure in areas such as the Himalayas, which is considered a biodiversity hotspot. Here, we investigated the phylogeographic structure and population dynamics of Primula tibetica by combining genomic phylogeography and species distribution models (SDMs). Genomic data were obtained for 293 samples of P. tibetica using restriction site-associated DNA sequencing (RADseq). Ensemble SDMs were carried out to predict potential present and past distribution ranges. Four distinct lineages were identified. Approximate Bayesian computation analyses showed that each of them have experienced both expansions and bottlenecks since their divergence, which occurred during or across the Quaternary glacial cycles. The two lineages at both edges of the distribution were found to be more vulnerable and responded in different ways to past climatic changes. These results illustrate how past climatic changes affected the demographic history of Himalayan organisms. Our findings highlight the significance of combining genomic approaches with environmental data when evaluating the effects of past climatic changes.

Approximate Bayesian Computation Reveals the Crucial Role of Oceanic Islands for the Assembly of Continental Biodiversity.

The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras.

Ecological niche models applied to post-megafire vegetation restoration in the context of climate change.

Climate change and land-use changes are the main drivers altering fire regimes and leading to the occurrence of megafires. Current management policies mainly focus on short-term restoration without considering how climate change might affect regeneration dynamics. We aimed to test the usefulness of ecological niche models (ENMs) to integrate the effects of climate change on tree species distributions into post-fire restoration planning. We also examined different important conceptual and methodological aspects during this novel process. We constructed ENM at fine spatial resolution (25 m) for the four main tree species (Pinus pinaster, Quercus pyrenaica, Q. faginea and Q. ilex) in an area affected by a megafire in Central Spain at two scales (local and regional), two periods (2 and 14 years after the fire) at the local scale, and under two future climate change scenarios. The usefulness of ENMs as support tools in decision-making for post-fire management was confirmed for the first time. As hypothesized, models developed at both scales are different, since they represent different scale dependent drivers of species distribution patterns. However, both provide objective information to be considered by stakeholders in combination with other sources of information. Local models generated with vegetation data 14 years after the fire provided valuable information about local and current vegetation dynamics (i.e., current microecology spatial niche prediction). Regional models are capable of considering a higher proportion of the climatic niche of species to generate reliable climate change forecasts (i.e., future macroclimate spatial niche forecast). The use of precise ENMs provide both an objective interpretation of potential habitat conditions and the opportunity of examining vegetation patches, that can be very valuable in managing restoration of areas affected by megafires under climate change conditions.

Botanical Collection Patterns and Conservation Categories of the Most Traded Timber Species from the Ecuadorian Amazon: The Role of Protected Areas.

The Ecuadorian Amazon is home to a rich biodiversity of woody plant species. Nonetheless, their conservation remains difficult, as some areas remain poorly explored and lack georeferenced records. Therefore, the current study aims predominantly to analyze the collection patterns of timber species in the Amazon lowlands of Ecuador and to evaluate the conservation coverage of these species in protected areas. Furthermore, we try to determine the conservation category of the species according to the criteria of the IUCN Red List. We identified that one third of the timber species in the study area was concentrated in three provinces due to historical botanical expeditions. However, a worrying 22.0% of the species had less than five records of presence, and 29.9% had less than ten records, indicating a possible underestimation of their presence. In addition, almost half of the species evaluated were unprotected, exposing them to deforestation risks and threats. To improve knowledge and conservation of forest biodiversity in the Ecuadorian Amazon, it is recommended to perform new botanical samplings in little-explored areas and digitize data in national herbaria. It is critical to implement automated assessments of the conservation status of species with insufficient data. In addition, it is suggested to use species distribution models to identify optimal areas for forest restoration initiatives. Effective communication of results and collaboration between scientists, governments, and local communities are key to the protection and sustainable management of forest biodiversity in the Amazon region.

The performance of protected-area expansions in representing tropical Andean species: past trends and climate change prospects.

Protected area (PA) extent has increased significantly over the last 150 years globally, but it is yet unclear whether progress in expanding coverage has been accompanied by improved performance in ecological representation. Here, we explore temporal trends in the performance of PA networks in representing > 16,000 vertebrate and plant species in tropical Andean countries based on species bioclimatic niche modelling. We use a randomization analysis to assess whether representation gains over time (1937-2015) are the expected consequence of increasing the overall area of the network or the result of better designed networks. We also explore the impact of climate change on protected-area representation based on projected species distributions in 2070. We found that PAs added in the last three to four decades were better at representing species diversity than random additions overall. Threatened species, amphibians and reptiles are the exception. Species representation is projected to decrease across PAs under climate change, although PA expansions over the last decade (2006-2015) better represented species' future bioclimatic niches than did sites selected at random for most evaluated groups. These findings indicate an unbalanced representation across taxa, and raises concern over under-represented groups, including threatened species, and species' representation under climate change scenarios. However, they also suggest that decisions related to locating protected areas have become more strategic in recent decades and illustrate that indicators tracking representativeness of networks are crucial in PA monitoring frameworks.

How do temperate bryophytes face the challenge of a changing environment? Lessons from the past and predictions for the future.

Bryophytes are a group of early land plants, whose specific ecophysiological and biological features, including poikilohydry, sensitivity to moderately high temperature and high dispersal ability, make them ideal candidates for investigating the impact of climate changes. Employing a combined approach of species distribution modelling (SDM) and molecular phylogeography in the temperate moss Homalothecium sericeum, we explore the significance of the Mediterranean refugia, contrasting the southern and northern refugia hypotheses, determine the extent to which recolonization of previously glaciated areas has been facilitated by the high dispersal ability of the species and make predictions on the extent to which it will be impacted by ongoing climate change. The Mediterranean areas exhibit the highest nucleotidic diversities and host a mixture of ancestral, endemic and more recently derived haplotypes. Extra-Mediterranean areas exhibit low genetic diversities and Euro-Siberian populations display a significant signal of expansion that is identified to be of Euro-Siberian origin, pointing to the northern refugia hypothesis. The SDMs predict a global net increase in range size owing to ongoing climate change, but substantial range reductions in southern areas. Presence of a significant phylogeographical signal at different spatial scales suggests, however, that dispersal limitations might constitute, as opposed to the traditional view of spore-producing plants as efficient dispersers, a constraint for migration. This casts doubts about the ability of the species to face the massive extinctions predicted in the southern areas, threatening their status of reservoir of genetic diversity.

Genomic analysis of Medicago ruthenica provides insights into its tolerance to abiotic stress and demographic history.

Medicago ruthenica has been recently cultivated as a new forage crop and has been recognized as a source of genes to improve abiotic stress tolerance in cultivated alfalfa because of its remarkable tolerance to drought, salinity-alkalinity, and cold and snowy winters. Here, we reveal a chromosome-scale genome sequence of M. ruthenica based on Illumina, PacBio, and Hi-C data. The assembled genome consists of 903.56 Mb with 50,268 annotated protein-coding genes, which is larger and contains relatively more genes than Medicago truncatula (420 Mb and 44,623 genes) and Medicago sativa spp. caerulea (793 Mb and 47,202 genes). All three species shared the ancestral Papilionoideae whole-genome duplication event before their divergence. The more recent expansion of repetitive elements compared to that in the other two species was determined to have contributed greatly to the larger genome size of M. ruthenica. We further found that multiple gene and transcription factor families (e.g., SOS homologous genes, NAC, C2H2, and CAMTA) have expanded in M. ruthenica, which might have led to its enhanced tolerance to abiotic stress. In addition, M. ruthenica harbors more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed two genetic lineages, reflecting the west and east of its geographical distribution, respectively. The two lineages probably diverged during the last glaciation and survived in multiple refugia at the last glacial maximum, followed by recent expansion. Our genomic data provide a genetic basis for further molecular breeding research on M. ruthenica and alfalfa.

Population Genetic Structure and Demographic History of Primula fasciculata in Southwest China.

Understanding the factors that drive the genetic structure of a species and its responses to past climatic changes is an important first step in modern population management. The response to the last glacial maximum (LGM) has been well studied, however, the effect of previous glaciation periods on plant demographic history is still not well studied. Here we investigated the population structure and demographic history of Primula fasciculata that widely occurs in the Hengduan Mountains and Qinghai-Tibetan Plateau. We obtained genomic data for 234 samples of the species using restriction site-associated DNA (RAD) sequencing and combined approximate Bayesian computation (ABC) and species distribution modeling (SDM) to evaluate the effects of multiple glaciation periods by testing several population divergence models and demographic scenarios. The analyses of population structure showed that P. fasciculata displays a striking population structure with six groups that could be identified genetically. Our ABC modeling suggested that the current groups diverged from ancestral populations located in the eastern Hengduan Mountains after the largest glaciation occurred in the region (~ 0.8-0.5 million years ago), which is consistent with the result of SDMs. Each current group has survived in different glacial refugia during the LGM and experienced expansions and/or bottlenecks since their divergence during or across the following Quaternary glacial cycles. Our study demonstrates the usefulness of population genomics for evaluating the effects of past climatic changes in alpine plant species with shallow population structure.

Biodiversity Models: What If Unsaturation Is the Rule?

Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions.

Climate threat on the Macaronesian endemic bryophyte flora.

Oceanic islands are of fundamental importance for the conservation of biodiversity because they exhibit high endemism rates coupled with fast extinction rates. Nowhere in Europe is this pattern more conspicuous than in the Macaronesian biogeographic region. A large network of protected areas within the region has been developed, but the question of whether these areas will still be climatically suitable for the globally threatened endemic element in the coming decades remains open. Here, we make predictions on the fate of the Macaronesian endemic bryophyte flora in the context of ongoing climate change. The potential distribution of 35 Macaronesian endemic bryophyte species was assessed under present and future climate conditions using an ensemble modelling approach. Projections of the models under different climate change scenarios predicted an average decrease of suitable areas of 62-87% per species and a significant elevational increase by 2070, so that even the commonest species were predicted to fit either the Vulnerable or Endangered IUCN categories. Complete extinctions were foreseen for six of the studied Macaronesian endemic species. Given the uncertainty regarding the capacity of endemic species to track areas of suitable climate within and outside the islands, active management associated to an effective monitoring program is suggested.

The mossy north: an inverse latitudinal diversity gradient in European bryophytes.

It remains hotly debated whether latitudinal diversity gradients are common across taxonomic groups and whether a single mechanism can explain such gradients. Investigating species richness (SR) patterns of European land plants, we determine whether SR increases with decreasing latitude, as predicted by theory, and whether the assembly mechanisms differ among taxonomic groups. SR increases towards the south in spermatophytes, but towards the north in ferns and bryophytes. SR patterns in spermatophytes are consistent with their patterns of beta diversity, with high levels of nestedness and turnover in the north and in the south, respectively, indicating species exclusion towards the north and increased opportunities for speciation in the south. Liverworts exhibit the highest levels of nestedness, suggesting that they represent the most sensitive group to the impact of past climate change. Nevertheless, although the extent of liverwort species turnover in the south is substantially and significantly lower than in spermatophytes, liverworts share with the latter a higher nestedness in the north and a higher turn-over in the south, in contrast to mosses and ferns. The extent to which the similarity in the patterns displayed by spermatophytes and liverworts reflects a similar assembly mechanism remains, however, to be demonstrated.

How to describe species richness patterns for bryophyte conservation?

A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in bryophyte conservation planning, and stacked species distribution models (S-SDMs) to produce reliable reconstructions of species richness patterns, given that differences between these methods have been insufficiently evaluated for inconspicuous taxa. Our objective was to contrast if species distribution models produce better inferences of diversity richness than simply selecting areas with the higher species numbers. As model species, we selected Iberian species of the genus Grimmia (Bryophyta), and we used four well-collected areas to compare and validate the following models: 1) four Maxent richness models, each generated without the data from one of the four areas, and a reference model created using all of the data and 2) four richness models obtained through direct spatial interpolation, each generated without the data from one area, and a reference model created with all of the data. The correlations between the partial and reference Maxent models were higher in all cases (0.45 to 0.99), whereas the correlations between the spatial interpolation models were negative and weak (-0.3 to -0.06). Our results demonstrate for the first time that S-SDMs offer a useful tool for identifying detailed richness patterns for inconspicuous taxa such as bryophytes and improving incomplete distributions by assessing the potential richness of under-surveyed areas, filling major gaps in the available data. In addition, the proposed strategy would enhance the value of the vast number of specimens housed in biological collections.

Modeling species distributions from heterogeneous data for the biogeographic regionalization of the European bryophyte flora.

The definition of biogeographic regions provides a fundamental framework for a range of basic and applied questions in biogeography, evolutionary biology, systematics and conservation. Previous research suggested that environmental forcing results in highly congruent regionalization patterns across taxa, but that the size and number of regions depends on the dispersal ability of the taxa considered. We produced a biogeographic regionalization of European bryophytes and hypothesized that (1) regions defined for bryophytes would differ from those defined for other taxa due to the highly specific eco-physiology of the group and (2) their high dispersal ability would result in the resolution of few, large regions. Species distributions were recorded using 10,000 km2 MGRS pixels. Because of the lack of data across large portions of the area, species distribution models employing macroclimatic variables as predictors were used to determine the potential composition of empty pixels. K-means clustering analyses of the pixels based on their potential species composition were employed to define biogeographic regions. The optimal number of regions was determined by v-fold cross-validation and Moran's I statistic. The spatial congruence of the regions identified from their potential bryophyte assemblages with large-scale vegetation patterns is at odds with our primary hypothesis. This reinforces the notion that post-glacial migration patterns might have been much more similar in bryophytes and vascular plants than previously thought. The substantially lower optimal number of clusters and the absence of nested patterns within the main biogeographic regions, as compared to identical analyses in vascular plants, support our second hypothesis. The modelling approach implemented here is, however, based on many assumptions that are discussed but can only be tested when additional data on species distributions become available, highlighting the substantial importance of developing integrated mapping projects for all taxa in key biogeographically areas of Europe, and the Mediterranean peninsulas in particular.

Do stacked species distribution models reflect altitudinal diversity patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.

Legume diversity patterns in West Central Africa: influence of species biology on distribution models.

OBJECTIVES: Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. METHODOLOGY: Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. RESULTS/CONCLUSIONS: Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused.