中国种子植物特有属的地理分布格局

生物特有现象的地理格局及其形成机制是生物地理学的重要研究内容.本文通过整合173个地区的中国种子植物特有属编目资料、环境和空间因子数据,运用多元回归和方差分解的方法,探索了中国种子植物特有属丰富度及其占全部种子植物属丰富度的比例(特有属比例)与环境(生境异质性和气候)和空间因子的关系.结果表明:(1)特有属丰富度及特有...     

Predicting species distributions in poorly-studied landscapes

Conservationists are increasingly relying on distribution models to predict where species are likely to occur, especially in poorly-surveyed but biodiverse areas. Modeling is challenging in these cases because locality data necessary for model formation are often scarce and spatially imprecise. To identify methods best suited to modeling in these conditions, we compared the success of three algorithms (Maxent, Mahalanobis Typicalities and Random Forests) at predicting distributions of eight bird and eight mammal species endemic to the eastern slopes of the central Andes. We selected study species to have a range of locality sample sizes representative of the data available for endemic species of this region and also that vary in their distribution characteristics. We found that for species that are known from moderate numbers (N = 38–94) of localities, the three methods performed similarly for species with restricted distributions but Maxent and Random Forests yielded better results for species with wider distributions. For species with small numbers of sample localities (N = 5–21), Maxent produced the most consistently successful results, followed by Random Forests and then Mahalanobis Typicalities. Because evaluation statistics for models derived from few localities can be suspect due to the poor spatial representation of the evaluation data, we corroborated these results with review by scientists familiar with the species in the field. Overall, Maxent appears to be the most capable method for modeling distributions of Andean bird and mammal species because of the consistency of results in varying conditions, although the other methods have strengths in certain situations. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The ability of climate envelope models to predict the effect of climate change on species distributions

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.     

A spider diversity model for the Caucasus Ecoregion

Precise information on spatial patterns of species richness and endemic species distribution is important for effective species conservation. In the Caucasus Ecoregion such information is virtually non-existent for invertebrate taxa. Using occurrence data from a large database we calculated species distribution models with the GARP algorithm for 471 spider species to visualize the diversity distribution of spider species in this region. Overall species diversity was highest in mountain forests of the North Caucasus, east-central Georgia, the southern slopes of the eastern Great Caucasus and south-east Azerbaijan. A regression tree analysis Chi squared automatic interaction detector method revealed the mean temperature of the driest quarter and precipitation parameters to be the main environmental factors shaping these patterns. Diversity of endemic species was correlated with overall species diversity but hotspots of endemic species (10+ percent of all species) exists in high-mountain areas, suggesting post-glacial speciation events in the high mountains as the main sources of high endemism in Caucasus. Further information on the spatial distribution of species diversity of invertebrate taxa in the Caucasus Ecoregion is needed to improve conservation efforts in this biodiversity hotspot.     

Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar

Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location Madagascar. Methods Models were developed and evaluated for 13 species of secretive leaf‐tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km² grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species.     

Fine‐scale patterns of species and phylogenetic turnover in a global biodiversity hotspot: Implications for climate change vulnerability

Question: What is the relative importance of environmental and spatial factors for species compositional and phylogenetic turnover? Location: High‐rainfall zone of the Southwest Australian Floristic Region (SWAFR). Methods: Correlates of species compositional turnover were assessed using quadrat‐based floristic data, and establishing relationships with environmental and spatial factors using canonical correspondence analyses and Mantel tests. Between‐quadrat phylogenetic distance measures were computed and examined for correlations with environmental and spatial attributes. Processes structuring pa2t2terns of beta diversity were also evaluated within four broad floristic assemblages defined a priori. Results: Floristic diversity was strongly related to environmental attributes. A low significance of spatial variables on assemblage patterns suggested no evident effect of dispersal limitations. Species compositional turnover was especially high within the swamp and outcrop assemblage. Phylogenetic turnover was closely coupled to species compositional turnover, implying the occurrence of many locally endemic and phylogenetically relict taxa. Beta diversity patterns within assemblages were also significantly correlated with the local environment, and relevant correlates differed between floristic assemblage types. Conclusion: Phylogenetic diversity in the SWAFR high‐rainfall zone is clustered within edaphic microhabitats in a generally subdued landscape. A clustered rather than dispersed distribution of phylogenetic diversity increases the probability of significant plant diversity loss during periods of climate change. Climate change susceptibility of the region's flora is accordingly estimated to be high. We highlight the conservation significance of swamp and outcrops that are characterized by distinct hydrological properties and may provide refugial habitat for plant diversity during periods of moderate climate change.     

Spatial patterns of phylogenetic diversity and endemism in the Western Ghats,India: A case study using ancient predatory arthropods

The Western Ghats (WG) mountain chain in peninsular India is a global biodiversity hotspot, one in which patterns of phylogenetic diversity and endemism remain to be documented across taxa. We used a well‐characterized community of ancient soil predatory arthropods from the WG to understand diversity gradients, identify hotspots of endemism and conservation importance, and highlight poorly studied areas with unique biodiversity. We compiled an occurrence dataset for 19 species of scolopendrid centipedes, which was used to predict areas of habitat suitability using bioclimatic and geomorphological variables in Maxent. We used predicted distributions and a time‐calibrated species phylogeny to calculate taxonomic and phylogenetic indices of diversity, endemism, and turnover. We observed a decreasing latitudinal gradient in taxonomic and phylogenetic diversity in the WG, which supports expectations from the latitudinal diversity gradient. The southern WG had the highest phylogenetic diversity and endemism, and was represented by lineages with long branch lengths as observed from relative phylogenetic diversity/endemism. These results indicate the persistence of lineages over evolutionary time in the southern WG and are consistent with predictions from the southern WG refuge hypothesis. The northern WG, despite having low phylogenetic diversity, had high values of phylogenetic endemism represented by distinct lineages as inferred from relative phylogenetic endemism. The distinct endemic lineages in this subregion might be adapted to life in lateritic plateaus characterized by poor soil conditions and high seasonality. Sites across an important biogeographic break, the Palghat Gap, broadly grouped separately in comparisons of species turnover along the WG. The southern WG and Nilgiris, adjoining the Palghat Gap, harbor unique centipede communities, where the causal role of climate or dispersal barriers in shaping diversity remains to be investigated. Our results highlight the need to use phylogeny and distribution data while assessing diversity and endemism patterns in the WG.     

Phytogeography of the Kaieteur Falls, Potaro Plateau, Guyana: floral distributions and affinities

Aim The plant diversity of one location on the Guiana Shield, Kaieteur National Park in Guyana, is used to examine the various hypothesized origins of the flora and to evaluate which may best explain the current plant distributions. Location Kaieteur National Park is located on eastern edge of the Potaro Plateau in central Guyana, South America. The species examined have distributions that vary from local to global. Methods The distribution patterns of the families, genera and species known from Kaieteur are examined using generalized distribution patterns. Results Data on distribution patterns, elevation and habitat were gathered from 131 flowering plant families, 517 genera and 1227 species. These plants represent all taxa that are currently known to occur in the area of the original Kaieteur National Park. Families tend to have cosmopolitan or pantropical distribution, genera are mostly neotropical and at the species level, most species are restricted to the Guiana Shield (c. 40%), northern South America (69%) or neotropical (96%) in distribution, each level inclusive of the previous. Conclusions The flora at the study site in Kaieteur National Park has its strongest affinity with the Guiana Shield; 42.1% of the species have a distribution that corresponds with the Shield or is more restricted within the Shield. There is a distinct flora on the Guiana Shield and its affinities lie with the flora of northern South American and beyond that, the neotropics. The flora is not closely affiliated with the floras of the Brazilian Shield, the Amazon, the Andes, the eastern coastal forests of Brazil, southern South America, or Africa as has been previous suggested.     

Modelling the occurrence of threatened plant species in taiga landscapes: methodological and ecological perspectives

Aim Understanding the spatial patterns of species distribution and predicting the occurrence of high biological diversity and rare species are central themes in biogeography and environmental conservation. The aim of this study was to model and scrutinize the relative contributions of climate, topography, geology and land‐cover factors to the distributions of threatened vascular plant species in taiga landscapes in northern Finland. Location North‐east Finland, northern Europe. Methods The study was performed using a data set of 28 plant species and environmental variables at a 25‐ha resolution. Four different stepwise selection algorithms [Akaike information criterion (AIC), Bayesian information criterion (BIC), adaptive backfitting, cross selection] with generalized additive models (GAMs) were fitted to identify the main environmental correlates for species occurrences. The accuracies of the distribution models were evaluated using fourfold cross‐validation based on the area under the curve (AUC) derived from receiver operating characteristic plots. The GAMs were tentatively extrapolated to the whole study area and species occurrence probability maps were produced using GIS techniques. The effect of spatial autocorrelation on the modelling results was also tested by including autocovariate terms in the GAMs. Results According to the AUC values, the model performance varied from fair to excellent. The AIC algorithm provided the highest mean performance (mean AUC = 0.889), whereas the lowest mean AUC (0.851) was obtained from BIC. Most of the variation in the distribution of threatened plant species was related to growing degree days, temperature of the coldest month, water balance, cover of mire and mean elevation. In general, climate was the most powerful explanatory variable group, followed by land cover, topography and geology. Inclusion of the autocovariate only slightly improved the performance of the models and had a minor effect on the importance of the environmental variables. Main conclusions The results confirm that the landscape‐scale distribution patterns of plant species can be modelled well on the basis of environmental parameters. A spatial grid system with several environmental variables derived from remote sensing and GIS data was found to produce useful data sets, which can be employed when predicting species distribution patterns over extensive areas. Landscape‐scale maps showing the predicted occurrences of individual or multiple threatened plant species may provide a useful basis for focusing field surveys and allocating conservation efforts.     

Predicting species richness and distribution ranges of centipedes at the northern edge of Europe

In recent decades, interest in understanding species distributions and exploring processes that shape species diversity has increased, leading to the development of advanced methods for the exploitation of occurrence data for analytical and ecological purposes. Here, with the use of georeferenced centipede data, we explore the importance and contribution of bioclimatic variables and land cover, and predict distribution ranges and potential hotspots in Norway. We used a maximum entropy analysis (Maxent) to model species' distributions, aiming at exploring centres of distribution, latitudinal spans and northern range boundaries of centipedes in Norway. The performance of all Maxent models was better than random with average test area under the curve (AUC) values above 0.893 and True Skill Statistic (TSS) values above 0.593. Our results showed a highly significant latitudinal gradient of increased species richness in southern grid-cells. Mean temperatures of warmest and coldest quarters explained much of the potential distribution of species. Predictive modelling analyses revealed that south-eastern Norway and the Atlantic coast in the west (inclusive of the major fjord system of Sognefjord), are local biodiversity hotspots with regard to high predictive species co-occurrence. We conclude that our predicted northward shifts of centipedes' distributions in Norway are likely a result of post-glacial recolonization patterns, species' ecological requirements and dispersal abilities.     

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.     

Imprints of glacial history and current environment on correlations between endemic plant and invertebrate species richness

Aim We evaluate how closely diversity patterns of endemic species of vascular plants, beetles, butterflies, molluscs and spiders are correlated with each other, and to what extent similar environmental requirements or survival in common glacial refugia and comparable dispersal limitations account for their existing congruence. Location Austria. Methods We calculated pairwise correlations among species numbers of the five taxonomic groups in 1405 cells of a 3′ × 5′ raster (c. 35 km²) using the raw data as well as the residuals of regression models that accounted for: (1) environmental variables, (2) environmental variables and the occurrence of potential refugia during the Last Glacial Maximum, or (3) environmental variables, refugia and spatial filters. Results Pairwise cross‐taxonomic group Spearman’s rank correlations in the raw data were significantly positive in most cases, but only moderate (0.3 < ρ < 0.5) to weak (ρ < 0.3) throughout. Correlations were closest between plants and beetles, plants and butterflies, and plants and snails, respectively, whereas the distribution of endemic spiders was largely uncorrelated with those of the other groups. Environmental variables explained only a moderate proportion of the variance in endemic richness patterns, and the response of individual groups to environmental gradients was only partly consistent. The inclusion of refugium locations and the spatial filters increased the goodness of model fit for all five taxonomic groups. Moreover, removing the effects of environmental conditions reduced congruence in endemic richness patterns to a lesser extent than did filtering the influence of refugium locations and spatial autocorrelation, except for spiders, which are probably the least dispersal‐limited of the five groups. Main conclusions The moderate to weak congruence of endemic richness patterns clearly limits the usefulness of a surrogacy approach for designating areas for the protection of regional endemics. On the other hand, our results suggest that dispersal limitations still shape the distributions of many endemic plant, snail, beetle and butterfly species, even at the regional scale; that is, survival in shared refugia and subsequent restricted spread retain a detectable signal in existing correlations. Concentrating conservation efforts on well‐known Pleistocene refugia hence appears to be a reasonable first step towards a strategy for protecting regional endemics of at least the less mobile invertebrate groups.     

Environmental and historical effects on richness and endemism patterns of carabid beetles in the western Palaearctic

Identifying determinants of spatial diversity gradients is in the focus of biodiversity-related research and has gained considerable importance regarding global change and conservation strategies. Despite their overwhelming diversity and the crucial role of invertebrates in ecosystem functioning, our understanding of factors driving broad-scale invertebrate diversity is limited. Tackling this issue, our study analyzes macroecological patterns of a highly diverse insect taxon across large parts of the western Palaearctic. We used regression modelling to assess the influence of environmental factors on overall, widespread and restricted-range (endemic) carabid beetle diversity. Single-term regressions and variation partitioning among climatic, topographic and spatial variables showed that total carabid diversity as well as richness patterns of widespread species were most strongly correlated with spatially structured variables related to current climate (measures of ambient energy and, to a lesser degree, precipitation and AET). In contrast, restricted-range (endemic) species were most notably related to range in elevation. We discuss the possible role of this factor as a surrogate measure of historical processes and the impact of history on contemporary diversity distributions. Our results indicate that while overall diversity patterns of carabids strongly reflect current climate conditions, this primarily reflects the more widespread species, whereas the spatial distribution of restricted-range species is still significantly affected by historical processes. Thus, for a general understanding of determinants and mechanisms of broad-scale diversity, taking into account dispersal abilities and range sizes of species is essential, especially as large parts of global biodiversity are represented by invertebrates with low dispersal powers.     

Where are the survivors? Tracking relictual populations of endangered frogs in Costa Rica

Aim We used abiotic environmental variables and historical locality records to infer distributions of endangered anuran species of Costa Rica to promote efficient strategies for future amphibian surveys. Location Costa Rica. Methods We used a Maximum Entropy Algorithm (Maxent) to predict potential distribution maps for 17 species of endangered anurans and create a consensus map of species richness. We compared the environmental conditions from localities where relictual amphibian populations were recently rediscovered with the conditions across their historical range to evaluate the possibility that these relictual populations might occur in specific climatic conditions that could explain their persistence. We used a multicriteria analysis considering the following factors: the intersection zones between the consensus map, conservation areas, potential Batrachochytrium dendrobatidis (Bd) distribution, collecting effort and areas within the precipitation range at which reappearances had occurred to locate sites for future surveys. Results The resulting predictions suggest that suitable areas for the highest number of species occur between 1300 and 2500 m.a.s.l and are concentrated along the Pacific slopes of the Cordillera de Talamanca and Cordillera Volcánica Central. Around 45% of the high potential richness area is under protection. Relictual populations of declined species seem to persist mainly in highly humid localities (2500–3500 mm of mean annual precipitation). Around 240 km² has an ideal environment for the rediscovery of relictual populations. The multicriteria analysis showed that around 0.5% of the Costa Rican territory should be surveyed exhaustively for frogs. Main conclusions Many of the potential refugia we identified here have not been surveyed since 2000, the areas identified by the best model predictions correspond well with the localities of the relictual populations recently reported. We suggest future surveys of missing amphibian species should focus on these areas. The discovery of populations of endangered species can be used to propose conservation areas.     

Continental shelf as potential retreat areas for Austral‐Asian estrildid finches (Passeriformes: Estrildidae) during the Pleistocene

Studies dealing with changes of biodiversity in time and space constitute an important part of biogeography, ecology and conservation biology. Areas of long‐term climate stability are particularly interesting as they might have facilitated the survival of species over historical times and thus are crucial for understanding contemporary diversity patterns. In this study, we assessed the potential distribution of 23 estrildid finch species in order to analyse stability in recent and past diversity patterns and diversity centres in the Austral‐Asiatic region. We used Maxent to predict recent distributions of each species and to project them onto the climatic conditions of the Last Glacial Maximum (LGM, 21 000 yr BP) using two different scenarios (CCSM, MIROC). The resulting diversity patterns were tested on presence and possible shifts of distribution centres. Diversity patterns of forest‐ and savannah‐living species were considered combined and separately. During the LGM, potential diversity patterns of forest‐living species corroborated well with postulated rainforest refuges situated on the eastern coast of Cape York Peninsula. Our results indicate a remarkably high stability of existing diversity centres. Although projections into the past show some differences in detail in the extent and exact position of the diversity centres, they reveal largely congruent large scale patterns in both time slices. However, the models suggest a northward shift towards exposed continental shelf areas that where dry during the LGM. Clearly, centres of diversity were situated on this land bridge between Australia and New Guinea, highlighting their importance as areas of retreat for estrildid finches and maybe other savannah species in times of changing climatic conditions and associated sea‐level fluctuations.     

Inferring climatic controls of rice stem borers’ spatial distributions using maximum entropy modelling

Accurate assessment of pest potential distributions is needed to identify their establishment risks that play a key role in pest management in agricultural ecosystems. We used a correlative niche modelling method (Maxent) to predict and map the spatial distributions of two important rice stem borers, Chilo suppressalis and Sesamia cretica, in paddy fields of Iran. In total, 195 presence occurrence records (101 records for C. suppressalis and 94 records for S. cretica) were compiled. A set of environmental and topographic variables, with the highest effects on the species distributions and the lowest correlations among themselves, were used. The results showed that mainly the northern parts of Iran were the most suitable areas for C. suppressalis, and north, north‐east and south‐west of Iran as the most suitable areas for S. cretica. Both models performed well, with an area under the receiver operating characteristic curve (AUC) of 0.983 and 0.786 for C. suppressalis and S. cretica, respectively. The Maxent models showed higher accuracy for predicting the distribution of the specialist pest with the small range sizes compared to the generalist species. Assessing the importance of environmental variables, which were derived from the jackknife test, showed the precipitation as the variable with the highest contribution (66%) in explaining the spatial distribution of C. suppressalis compared to the other variables. The distribution of S. cretica was influenced by a set of variables derived from both the precipitation and temperature. The Maxent predictions were useful to map the geographical distributions of the risk for both rice stem borers that is needed to develop effective management strategies.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

Pleistocene refugium endemics exhibit greater allozymic diversity than widespread congeners in the genus Polygonella (Polygonaceae)

Populations of each of the 11 species of the North American angiosperm genus Polygonella (Polygonaceae) were sampled for electrophoretically detectable allozyme diversity. In contrast to expectations based on similar surveys in many other vascular plant groups, the two most widespread species of Polygonella showed reduced within-population gene diversity with respect to their narrowly endemic congeners. One possible explanation is that high levels of selfing in the widespread species have led to reduced population-level diversity. An alternative explanation is that large-scale migration during Pleistocene glaciations removed much of the diversity of these more northerly distributed species, while the endemics, several of which inhabit known Pleistocene refugia, were able to maintain higher levels of diversity because of population stability during the glacial cycles. If the latter explanation is correct, an important implication for conservation is that, for many genera in eastern North America, the species richest in gene diversity may be those most in danger of extirpation in the next decade, namely those species endemic to Pleistocene refugia such as the Lake Wales Ridge.     

Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China

Aims Predicting suitable habitat distribution is an effective way to protect rare or endangered medicinal plants. Cornus officinalis is a perennial tree growing in forest edge and its air-dried pericarp is one of the traditional Chinese medicines (TCM) with significant medicinal values. In recent years, C. officinalis has undergone severe degeneration of its natural habitat owing to growing market demands and unprecedented damage to the forests. Moreover, the degeneration of suitable habitat has threatened the supply of medicinal materials, and even led to the extinction of some engendered medicinal plant species. In this case, there is a great risk to introduce and cultivate medicinal plants if planners determine the suitable cultivation regions based on personal subjective experience alone. Therefore, predicting suitable potential habitat distribution of medicinal plants (e.g. C. officinalis) and revealing the environmental factors determining such distribution patterns are important to habitat conservation and environmental restoration.Methods In this article, we report the results of a study on the habitat distribution of C. officinalis using maximum entropy (Maxent) modeling and fuzzy logics together with loganin content and environmental variables. The localities of 106 C. officinalis in China were collected by our group and other researchers and used as occurrence data. The loganin content of 234 C. officinalis germplasm resources were tested by high-performance liquid chromatography (HPLC) and used as content data. 79 environmental variables were selected and processed with multicollinearity test by using Pearson Correlation Coefficient (r) to determine a set of independent variables. The chosen variables were then processed in the fuzzy linear model according to the cell values (maximum, minimum) of localities with estimated loganin content. The SDMtoolbox was used to spatially rarefy occurrence data and prepare bias files. Furthermore, combined Maxent modeling and fuzzy logics were used to predict the suitable habitat of C. officinalis. The modeling result was validated using null-model method.Important findings As a result, six environmental factors including tmin3, prec3, bio4, alt, bio12 and bio3 were determined as key influential factors that mostly affected both the habitat suitability and active ingredient of C. officinalis. The highly suitable regions of C. officinalis mainly distribute in a 'core distribution zone' of the east-central China. The statistically significant AUC value indicated that combined Maxent modeling and fuzzy logics could be used to predict the suitable habitat distribution of medicinal plants. Furthermore, our results confirm that ecological factors played critical roles in assessing suitable geographical regions as well as active ingredient of plants, highlighting the need for effective habitat rehabilitation and resource conservation.     

The effect of sample size and species characteristics on performance of different species distribution modeling methods

Species distribution models should provide conservation practioners with estimates of the spatial distributions of species requiring attention. These species are often rare and have limited known occurrences, posing challenges for creating accurate species distribution models. We tested four modeling methods (Bioclim, Domain, GARP, and Maxent) across 18 species with different levels of ecological specialization using six different sample size treatments and three different evaluation measures. Our assessment revealed that Maxent was the most capable of the four modeling methods in producing useful results with sample sizes as small as 5, 10 and 25 occurrences. The other methods compensated reasonably well (Domain and GARP) to poorly (Bioclim) when presented with datasets of small sample sizes. We show that multiple evaluation measures are necessary to determine accuracy of models produced with presence-only data. Further, we found that accuracy of models is greater for species with small geographic ranges and limited environmental tolerance, ecological characteristics of many rare species. Our results indicate that reasonable models can be made for some rare species, a result that should encourage conservationists to add distribution modeling to their toolbox.