Predicting potential distribution and evaluating biotic interactions of threatened species: a case study of Discocactus ferricola (Cactaceae)

Information on distribution, number of populations, and biotic interactions are essential for assessing the threat status of species and to establish more effective conservation initiatives. Ecological niche modeling have been successfully applied to identify the potential distribution, even for rare species that have few recorded occurrence points. In this study, we evaluated the potential distribution and additionally generated the first data on the reproductive biology of Discocactus ferricola, due to its degree of threat and the absence of ecological data for that species. The potential distribution map highlighted areas with higher probability of occurrence of D. ferricola on the Residual Plateau of Maciço do Urucum located in Mato Grosso do Sul, Brazil. The occurrence of D. ferricola populations was limited to outcrops of flat ironstone (cangas) distributed in patches across the landscape, increasing the chances of serious threats, such as habitat loss due to mining and species extraction. We also found that D. ferricola is xenogamous. Therefore, in situ conservation actions must prioritize the maintenance of interactions with pollinators by preserving the flora and fauna of rocky outcrops and adjacent forests in areas of greater environmental suitability for D. ferricola. Our study highlights the use of ecological niche modeling and data on biotic interactions to evaluate species potential distribution, to guide new sampling efforts, and to assist conservation and management initiatives.

A Contribution to the Biogeography of Ablepharus anatolicus and A. budaki (Squamata: Scincidae) Using Ecological Niche Modeling in Turkey

The Anatolian Peninsula is very richly biodiverse in terms of its location and with new studies, this wealth has gradually increased as new taxa of Anatolian origin are added to the literature. Ablepharus budaki and A. anatolicus, formerly considered to be subspecies of A. kitaibelli and A. budaki respectively, are spread throughout the southern part of Anatolia. Although recent phylogenetic and morphological studies revealed their species status, no information was given about the relation of the species with each other in terms of ecological niche. In this study, our primary goal was to discover whether the niches of these two taxa were different from each other. Considering the analyses made within the scope of this study, it has been revealed that both A. anatolicus and A. budaki are different from each other in terms of their ecological niche. However, since these two taxa have very small contact regions, an example of parapatric speciation, and their distribution areas cover almost completely different geographies, we can say that they have different ecological niche requirements, according to the results of this study. As a result, this study supported the findings in literature and the idea that these taxa are two different species

Geographic Distribution of Colombian Spittlebugs (Hemiptera: Cercopidae) via Ecological Niche Modeling: A Prediction for the Main Tropical Forages' Pest in the Neotropics

Spittlebugs (Hemiptera: Cercopidae) are the main tropical pests in Central and South America of cultivated pastures. We aimed to estimate the potential distribution of Aeneolamia varia, A. lepidior, A. reducta, Prosapia simulans, Zulia carbonaria, and Z. pubescens throughout the Neotropics using ecological niche modeling. These six insect species are common in Colombia and cause large economic losses. Records of these species, prior to the year 2000, were compiled from human observations, specimens from CIAT Arthropod Reference Collection (CIATARC), Global Biodiversity Information Facility (GBIF), speciesLink (splink), and an extensive literature review. Different ecological niche models (ENMs) were generated for each species: Maximum Entropy (MaxEnt), generalized linear (GLM), multivariate adaptive regression spline (MARS), and random forest model (RF). Bioclimatic datasets were obtained from WorldClim and the 19 available variables were used as predictors. Future changes in the potential geographical distribution were simulated in ENMs generated based on climate change projections for 2050 in two scenarios: optimistic and pessimistic. The results suggest that (i) Colombian spittlebugs impose an important threat to Urochloa production in different South American countries, (ii) each spittlebug species has a unique geographic distribution pattern, (iii) in the future the six species are likely to invade new geographic areas even in an optimistic scenario, (iv) A. lepidior and A. reducta showed a higher number of suitable habitats across Colombia, Venezuela, Brazil, Peru, and Ecuador, where predicted risk is more severe. Our data will allow to (i) monitor the dispersion of these spittlebug species, (ii) design strategies for integrated spittlebug management that include resistant cultivars adoption to mitigate potential economic damage, and (iii) implement regulatory actions to prevent their introduction and spread in geographic areas where the species are not yet found.

Molecular evidence and ecological niche modeling reveal an extensive hybrid zone among three Bursera species (section Bullockia)

The genus Bursera, includes ~100 shrub and trees species in tropical dry forests with its center of diversification and endemism in Mexico. Morphologically intermediate individuals have commonly been observed in Mexican Bursera in areas where closely related species coexist. These individuals are assumed to result from interspecific hybridization, but no molecular evidence has supported their hybrid origins. This study aimed to investigate the existence of interspecific hybridization among three Mexican Bursera species (Bullockia section: B. cuneata, B. palmeri and B. bipinnata) from nine populations based on DNA sequences (three nuclear and four chloroplast regions) and ecological niche modeling for three past and two future scenario projections. Results from the only two polymorphic nuclear regions (PEPC, ETS) supported the hybrid origin of morphologically intermediate individuals and revealed that B. cuneata and B. bipinnata are the parental species that are genetically closer to the putative hybrids. Ecological niche modeling accurately predicted the occurrence of putative hybrid populations and showed a potential hybrid zone extending in a larger area (74,000 km2) than previously thought. Paleo-reconstructions showed a potential hybrid zone existing from the Last Glacial Maximum (~ 21 kya) that has increased since the late Holocene to the present. Future ecological niche projections show an increment of suitability of the potential hybrid zone for 2050 and 2070 relative to the present. Hybrid zone changes responded mostly to an increase in elevational ranges. Our study provides the first insight of an extensive hybrid zone among three Mexican Bursera species based on molecular data and ecological niche modeling.

Climatic curves as predictors in MaxEnt niche modeling

Environmental niche modelling (ENM) uses different types of variables to predict species occurrence. In widespread use are variables derived from climatic curves, i.e., average annual changes in some climatic parameter. This study shows how to use the climatic curves themselves as ENM predictors. The key step is projection of the curves' constituent variables on a suitable spline basis, which preserves time-ordering of the variables and supports smoothness of predictions. Complexity of the model is controlled by sensible choice of the spline basis, followed by lasso regularization in model fitting.

Natural Hybrid Origin of the Controversial “Species” Clematis × pinnata (Ranunculaceae) Based on Multidisciplinary Evidence

Interspecific hybridization is common and has often been viewed as a driving force of plant diversity. However, it raises taxonomic problems and thus impacts biodiversity estimation and biological conservation. Although previous molecular phylogenetic studies suggested that interspecific hybridization may be rather common in Clematis, and artificial hybridization has been widely applied to produce new Clematis cultivars for nearly two centuries, the issue of natural hybridization of Clematis has never been addressed in detail. In this study, we tested the hybrid origin of a mesophytic and cold-adapted vine species, Clematis pinnata, which is a rare and taxonomically controversial taxon endemic to northern China. Using field investigations, flow cytometry (FCM), phylogenomic analysis, morphological statistics, and niche modeling, we tested hybrid origin and species status of C. pinnata. The FCM results showed that all the tested species were homoploid (2n = 16). Phylonet and HyDe analyses based on transcriptome data showed the hybrid origins of C. × pinnata from either C. brevicaudata × C. heracleifolia or C. brevicaudata × C. tubulosa. The plastome phylogeny depicted that C. × pinnata in different sampling sites originated by different hybridization events. Morphological analysis showed intermediacy of C. × pinnata between its putative parental species in many qualitative and quantitative characters. Niche modeling results suggested that C. × pinnata had not been adapted to a novel ecological niche independent of its putative parents. These findings demonstrated that plants of C. × pinnata did not formed a self-evolved clade and should not be treated as a species. The present study also suggests that interspecific hybridization is a common mechanism in Clematis to generate diversity and variation, and it may play an important role in the evolution and diversification of this genus. Our study implies that morphological diversity caused by natural hybridization may overstate the real species diversity in Clematis.

Ensemble ecological niche modeling of West Nile virus probability in Florida

Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model was created through the weighted averaging of three separate machine learning models—boosted regression tree, random forest, and maximum entropy—developed for this study using sentinel chicken surveillance and remote sensing data. Variable importance differed among the models. The highest variable permutation value included mean dewpoint temperature for the boosted regression tree model, mean temperature for the random forest model, and wetlands focal statistics for the maximum entropy mode. Model validation resulted in area under the receiver curve predictive values ranging from good [0.8728 (95% CI 0.8422–0.8986)] for the maximum entropy model to excellent [0.9996 (95% CI 0.9988–1.0000)] for random forest model, with the ensemble model predictive value also in the excellent range [0.9939 (95% CI 0.9800–0.9979]. This model should allow mosquito control districts to optimize West Nile virus surveillance, improving detection and allowing for a faster, targeted response to reduce West Nile virus transmission potential.