Application of parsimony analysis of endemicity to Mexican gymnosperm distributions: grid-cells, biogeographical provinces and track analysis

Neuroptera Diversity from Tacaná Volcano, Mexico: Species Composition, Altitudinal and Biogeographic Pattern of the Fauna

Approximately 340 species of ten families of Neuroptera have been recorded from Mexico. The Tacaná volcano, reaching an elevation of 4092 m a.s.l., is the northernmost representative of the Central American Nucleus volcanic range. Recent survey efforts of the Neuroptera diversity of the Tacaná volcano, Chiapas, along an altitudinal gradient, increased the known fauna of this order in Mexico by 31 species and two genera: Biramus Oswald, 1993 (Hemerobiidae), and Titanochrysa Sosa & Freitas, 2012 (Chrysopidae), with extension of the known distributional range of 25 species of five families. Most of the new country records are from species previously known only from Central and South America. The lacewing fauna of Chiapas is updated from 91 to 147 species. The Neuroptera of the Tacaná volcano is mostly Neotropical with some taxa of Nearctic affinity restricted to medium and high elevations. More than 80% of the Tacaná volcano lacewing species also occur in the Brazilian subregion, especially the Mesoamerican and Pacific domains. Neuropteran species were recorded from 650 to more than 3500 m a.s.l. A higher species richness was present between 600 and 1700 m, with a few species occurring at altitudes above 3000 m. A species checklist and an identification key to the genera of Neuroptera of the Tacaná volcano are provided.

Geographical sampling bias on the assessment of endemism areas for marine meiobenthic fauna

Species distribution patterns are constrained by historical and ecological processes in space and time, but very often the species range sizes are geographical sampling biases resulting from unequal sampling effort. One of the most common definitions of endemism is based on the "congruence of distributional areas" criterion, when two or more species have the same distributional limits. By acknowledging that available data of marine meiobenthic species are prone to geographical sampling bias and that can affect the accuracy of the biogeographical signals, the present study combines analyses of inventory incompleteness and recognition of spatial congruence of Gastrotricha, Kinorhyncha, meiobenthic Annelida and Tardigrada in order to better understand the large-scale distribution of these organisms in coastal and shelf areas of the world. We used the marine bioregionalization framework for geographical operative units to quantify the inventory incompleteness effect (by modelling spatial predictions of species richness) and to recognize areas of endemism. Our models showed that the difference between observed and expected species richness in the Southern Hemisphere is much higher than in the Northern Hemisphere. Parsimony Analysis of Endemicity delimited 20 areas of endemism, most found in the Northern Hemisphere. Distribution patterns of meiobenthic species are shown to respond to events of geographical barriers and abiotic features, and their distribution is far from homogeneous throughout the world. Also, our data show that ecoregions with distinct biotas have at least some cohesion over evolutionary time. However, we found that inventory incompleteness may significantly affect the explanatory power of areas of endemism delimitation in both hemispheres. Yet, whereas future increases in sampling efforts are likely to change the spatial congruence ranges in the Southern Hemisphere, patterns for the Northern Hemisphere may prove to be relatively more resilient.

New approaches to the biogeography and areas of endemism of red oaks (Quercus L., section Lobatae)

An area of endemism is defined by the spatial congruence among two or more species with distributions that are limited by barriers. In this study, we explored and discussed the use of the network analysis method (NAM) and neighbor-joining (NJ) to analyze the areas of endemism of Quercus sect. Lobatae (red oak species) in Mexico and Central America. We compared the NAM and NJ with other methods commonly used in biogeographic studies to show the advantages of these new approaches and to identify the shortcomings of other approaches. The NAM used in this study is based on notions of centrality measures, such as betweenness. We incorporated the strength of the ties within the internal networks through p-cores and aggregate constraints in iterative analyses. The NAM based on betweenness is ideal for recognizing completely allopatric areas of endemism. The iterative NAMs increase the number of possible areas of endemism because they minimize the effect of minimal overlap, and the p-core is efficient at identifying the closest relationships among species in the cases in which betweenness is not informative. The number of areas of endemism increases when the sympatry matrix minimizes the dispersal effect and the sample effort is maximized, allowing the identification of the greatest number of these areas. The NJ method supports the idea that areas diverge among themselves in a differential way; the long branches correspond to zones with high speciation rates and complex histories (biotic and tectonic), and the short branches correspond to zones with low speciation rates and simple histories. In a classification scheme, NJ was capable of identifying the areas that are considered biotically complex because of their high speciation rates. The results obtained with the NAM and NJ showed that the physiographic regions of Mexico are not natural units and that many of them are composed of at least two different biotic components.

A maximum likelihood approach to generate hypotheses on the evolution and historical biogeography in the Lower Volga Valley regions (southwest Russia)

The evolution of the diverse flora in the Lower Volga Valley (LVV) (southwest Russia) is complex due to the composite geomorphology and tectonic history of the Caspian Sea and adjacent areas. In the absence of phylogenetic studies and temporal information, we implemented a maximum likelihood (ML) approach and stochastic character mapping reconstruction aiming at recovering historical signals from species occurrence data. A taxon-area matrix of 13 floristic areas and 1018 extant species was constructed and analyzed with RAxML and Mesquite. Additionally, we simulated scenarios with numbers of hypothetical extinct taxa from an unknown palaeoflora that occupied the areas before the dramatic transgression and regression events that have occurred from the Pleistocene to the present day. The flora occurring strictly along the river valley and delta appear to be younger than that of adjacent steppes and desert-like regions, regardless of the chronology of transgression and regression events that led to the geomorphological formation of the LVV. This result is also supported when hypothetical extinct taxa are included in the analyses. The history of each species was inferred by using a stochastic character mapping reconstruction method as implemented in Mesquite. Individual histories appear to be independent from one another and have been shaped by repeated dispersal and extinction events. These reconstructions provide testable hypotheses for more in-depth investigations of their population structure and dynamics.