Distributional patterns of the Neotropical humid montane forest avifaunas

The study of biogeographical patterns of the Neotropical humid montane forest avifauna has been prevented due to the lack of phylogenetic hypotheses for most taxa, and to the paucity of detailed studies about the geographical distribution for most of the species. Distributional patterns of this avifauna were explored by integrating predictive distributional models and Parsimony Analysis of Endemicity (PAE). Distributional maps were generated using the Genetic Algorithms for Rule Set Prediction for 442 species; this information was transformed into a data matrix for analysis with PAE. Hierarchical information corresponding to the genus level was incorporated to help resolve the relationships between areas. A strict consensus cladogram showed a clear separation between the Mesoamerican and South American avifaunas. Within the Mesoamerican clade, three geographically structured groups were obtained, whereas the South American clade showed a polytomy of three groups, with two of them, the South Andean Yungas and the Tepuis, located outside the main clade. The third group is a well resolved clade, including areas from eastern Panama and northern Venezuela to central Bolivia. Area relationships suggest a mixed history of dispersal and vicariant events, with the latter being the most important for explaining the biogeographical patterns found.  © 2008 The Linnean Society of London, Biological Journal of the Linnean Society , 2008, 94 , 175–194.     

The influence of temporal variation on relationships between ecosystem services

A growing literature aims to identify areas of congruence in the provision of multiple ecosystem goods and services. However, little attention has been paid to the effect that temporal variation in the provision of such services may have on understanding of these relationships. Due to a lack of temporally and spatially replicated monitoring surveys, such relationships are often assessed using data from disparate time periods. Utilising temporally replicated data for indices of freshwater quality and agricultural production we demonstrate that through time the biophysical values of ecosystem services may vary in a spatially non-uniform way. This can lead to differing conclusions being reached about the strength of relationships between services, which in turn has implications for the prioritisation of areas for management of multiple services. We present this first analysis to illustrate the effect that the use of such temporally disparate datasets may have, and to highlight the need for further research to assess under what circumstances temporal variation of this sort will have the greatest impact.     

Cladistic biogeography and the art of discovery

Aims

Cladistic biogeography is about discovering geographical congruence. The agreement of several taxon‐area cladograms (TACs) rarely yields a perfect result. Areas may overlap, taxa may not be evenly distributed, and thus, ambiguity may be prevalent in the data. Ambiguity is incongruence and may be resolved by reducing paralogy and resolving potential information. Recently, several new approaches in cladistic biogeography [i.e. Brooks parsimony analysis (BPA), Assumption 0] interpret ambiguity as congruence. These methods are problematic, as they are generational. Methods constructed under the generation paradigm are flawed concepts that are immunized from falsifying evidence. A critique of modified BPA reveals that taking an evolutionary stance in biogeography leads to flaws in implementation.

Methods

Area cladistics is a new development in cladistic biogeography. Area cladistics adopts paralogy‐free subtree analysis using Assumption 2, to discover the relative positions of continents through time.

Results

Geographical congruence is the result of allopatric (geographical) speciation. Vicariance, dispersal and combinations of both, are recognized causes for allopatric speciation. Area cladistics highlights the concept that all these events occur in response to geological changes (e.g. continental drift) either directly, by geographical boundaries, or indirectly, at the level of ocean currents. Samples of chosen examples all respond to the geological process. The examples include Ordovician–Silurian and Lower Devonian trilobites to yield a general areagram which is a representational branching diagram that depicts the relationships of areas.

Main conclusion

Finding one common biogeographical pattern from several unrelated groups is a qualitative approach to interpret the positions of continental margins through time. Area cladistics is not a substitute for palaeomaps that are derived from palaeomagnetic data, but general areagrams adding to the body of knowledge that yields more precise interpretations of the earth's past.

     

Areas of endemism of Mexican mammals: reanalysis applying the optimality criterion

In order to test Mexican areas of endemism of mammals identified by previous parsimony analyses of endemicity (PAEs), we applied the optimality criterion to three data matrices (based on point records, potential distributional models and the fill option in software NDM). We modelled the ecological niches of 429 terrestrial mammal species using the genetic algorithm for rule-set prediction (GARP) and models were projected as potential distributional areas. We overlapped the point occurrence data and the individual maps of potential distributions to a grid of 1° latitude–longitude. Three matrices of 247 grid cells (areas) and 429 species were built: (1) a binary matrix with '0' for absence and '1' for presence of at least one record of the species inside the grid-cell; (2) a three-state matrix similar to (1) but assigning the state '2' to the assumed presence in the model of potential distribution; and (3) a three-state matrix similar to (2), but applying the fill option of software NDM instead of using a model. The optimality criterion was performed in NDM version 2.7 and results were examined with VNDM version 2.7. The first and second matrices showed 13 areas of endemism and the third identified 16 areas of endemism. NDM provided a better resolution than PAE, allowing us to identify several new areas of endemism, previously undetected. Ecological niche models, projected as potential distributional areas, and the optimality criterion are very useful to identify areas of endemism, although they should be used with caution because they may overpredict potential distributional areas. PAE seems to underestimate the areas of endemism identified.  © 2009 The Linnean Society of London, Biological Journal of the Linnean Society , 2009, 98 , 468–478.     

Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment

Generalized dissimilarity modelling (GDM) is a statistical technique for analysing and predicting spatial patterns of turnover in community composition (beta diversity) across large regions. The approach is an extension of matrix regression, designed specifically to accommodate two types of nonlinearity commonly encountered in large-scaled ecological data sets: (1) the curvilinear relationship between increasing ecological distance, and observed compositional dissimilarity, between sites; and (2) the variation in the rate of compositional turnover at different positions along environmental gradients. GDM can be further adapted to accommodate special types of biological and environmental data including, for example, information on phylogenetic relationships between species and information on barriers to dispersal between geographical locations. The approach can be applied to a wide range of assessment activities including visualization of spatial patterns in community composition, constrained environmental classification, distributional modelling of species or community types, survey gap analysis, conservation assessment, and climate-change impact assessment.     

Misconceptions about parsimony analysis of endemicity

Parsimony analysis of endemicity (PAE) has been widely criticized in the recent literature based on methodology rather than on theory. Here I argue that most of the criticisms of PAE result from confusion between the dynamic and static approaches of PAE, by both users and critics of the method. Originally, PAE (the dynamic approach) was proposed primarily for historical comparisons of biotic distributions based on geological and stratigraphical information; that is, the stratigraphical record of the biota within two or more horizons was used to evaluate changes (layer by layer) in their distributional patterns. This led to an analysis of the biota throughout space and through time. On the other hand, the static approach excluded the temporal component and based the analysis on a single geological horizon. Most problems exemplified and discussed in the literature refer to the static approach. In addition to this defence of the original PAE, I present some new criticisms regarding the application of PAE using artificially delimited areas (for example areas defined by geopolitical boundaries), which may lead to incorrect interpretations. Recently, several variations of static PAE have appeared: some designed to accommodate ecological data (e.g. parsimony analysis of distributions – PAD); others that incorporate phylogenetic content (e.g. cladistic analysis of distributions and endemism – CADE); and some that have been integrated with other historical methods (e.g. panbiogeography) in order to detect and evaluate hypotheses of biogeographical homologies. Biogeographers, both ecological and historical, should be aware of the problems and limitations of both dynamic and static PAE and evaluate new variations of PAE (PAD, CADE, etc.). Finally, I argue in favour of an independent and pluralist discipline of biogeography that treats biogeography as related to systematics but not dependent on it, as some scholars have assumed.     

Inferring the geographic origin of a range expansion: Latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program x‐origin

Climatic or environmental change is not only driving distributional shifts in species today, but it has also caused distributions to expand and contract in the past. Inferences about the geographic locations of past populations especially regions that served as refugia (i.e., source populations) and migratory routes are a challenging endeavour. Refugial areas may be evidenced from fossil records or regions of temporal stability inferred from ecological niche models. Genomic data offer an alternative and broadly applicable source of information about the locality of refugial areas, especially relative to fossil data, which are either unavailable or incomplete for most species. Here, we present a pipeline we developed (called x ‐origin ) for statistically inferring the geographic origin of range expansion using a spatially explicit coalescent model and an approximate Bayesian computation testing framework. In addition to assessing the probability of specific latitudinal and longitudinal coordinates of refugial or source populations, such inferences can also be made accounting for the effects of temporal and spatial environmental heterogeneity, which may impact migration routes. We demonstrate x ‐origin with an analysis of genomic data collected in the Collared pika that underwent postglacial expansion across Alaska, as well as present an assessment of its accuracy under a known model of expansion to validate the approach.     

Cladistic analysis of distributions and endemism (CADE): using raw distributions of birds to unravel the biogeography of the South American aridlands

Aim To use published distributional and taxonomic information on Neotropical birds in a cladistic analysis of distributions and endemism (CADE) to generate a testable hypothesis of area‐relationships for the arid areas of endemism, particularly those of Central South America (the ‘arid diagonal’), and to clarify the different methodologies commonly associated with parsimony analysis of endemicity (PAE). Location South America. Methods Cladistic analysis of distributions and endemism. Results We obtain a tree where the relationships of most areas are resolved, and we find support for an exclusive clade of Central South American areas, with the Caatinga as sister to both the Chaco and Cerrado. Main conclusions There is a substantial amount of historical signal in avian distributions, when large numbers of taxa and multiple taxonomic levels are considered. Ecological noise and historical information are more easily distinguished in CADE analyses than they would be in PAE analyses. Based on our results we predict that among aridland birds, the Cerrado and Chaco species will be more closely related to each other than to Caatinga species.     

Semiparametric maximum likelihood for measurement error model regression

This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural model is used in which probability distributions are specified for (a) the response and (b) the measurement error. A distribution is also assumed for the true explanatory variable but is left unspecified and is estimated by nonparametric maximum likelihood. For various types of extra information about the measurement error distribution, the proposed algorithm makes use of available routines that would be appropriate for likelihood analysis of (a) and (b) if the true x were available. Simulations suggest that the semiparametric maximum likelihood estimator retains a high degree of efficiency relative to the structural maximum likelihood estimator based on correct distributional assumptions and can outperform maximum likelihood based on an incorrect distributional assumption. The approach is illustrated on three examples with a variety of structures and types of extra information about the measurement error distribution.     

Do the Oaxacan Highlands represent a natural biotic unit? A cladistic biogeographical test based on vertebrate taxa

Aim  We analysed the distributional patterns of six terrestrial vertebrate taxa from the Oaxacan Highlands (Sierra Mazateca, Nudo de Zempoaltépetl and Sierra de Juárez) through a cladistic biogeographical approach, in order to test their naturalness as a biotic unit.
Location  The Oaxacan Highlands, Mexico.
Methods  The cladistic biogeographical analysis was based on the area cladograms of the Pseudoeurycea bellii species group (Amphibia: Plethodontidae), the genus Chlorospingus (Aves: Thraupidae), the genera Microtus , Reithrodontomys and Habromys , and the Peromyscus aztecus species group (Mammalia: Rodentia). We obtained paralogy-free subtrees, from which the components were coded in a data matrix for parsimony analysis. The data matrix was analysed with N ona through W in C lada .
Results  The parsimony analysis resulted in a single general area cladogram in which areas were fragmented following the sequence Sierra Madre Occidental, Trans-Mexican Volcanic Belt, Chiapas, Sierra Madre Oriental + Sierra Mazateca, Sierra Madre del Sur, Nudo de Zempoaltépetl and Sierra de Juárez.
Main conclusions  The general area cladogram shows that the Oaxacan Highlands do not constitute a natural unit. The Sierra Mazateca is the sister area to the Sierra Madre Oriental, whereas the Nudo de Zempoaltépetl and the Sierra de Juárez are closely related to the Sierra Madre del Sur. The events that might have caused these patterns include cycles of expansion and contraction of mountain pinyon, juniper and oak woodlands during the Pleistocene.     

Assigning precursor–product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies

Tandem mass spectrometry using precursor ion selection (MS/MS) is an invaluable tool for structural elucidation of small molecules. In non-targeted metabolite profiling studies, instrument duty cycle limitations and experimental costs have driven efforts towards alternate approaches. Recently, researchers have begun to explore methods for collecting indiscriminant MS/MS (idMS/MS) data in which the fragmentation process does not involve precursor ion isolation. While this approach has many advantages, importantly speed, sensitivity and coverage, confident assignment of precursor–product ion relationships is challenging, which has inhibited broad adoption of the technique. Here, we present an approach that uses open source software to improve the assignment of precursor–product relationships in idMS/MS data by appending a dataset-wide correlational analysis to existing tools. The utility of the approach was demonstrated using a dataset of standard compounds spiked into a malt-barley background, as well as unspiked human serum. The workflow was able to recreate idMS/MS spectra which are highly similar to standard MS/MS spectra of authentic standards, even in the presence of a complex matrix background. The application of this approach has the potential to generate high quality idMS/MS spectra for each detectable molecular feature, which will streamline the identification process for non-targeted metabolite profiling studies.     

Structural and floristic behaviors in East Timor forest vegetation

Owing to the growing demand for the products supplied and to the slowness of their renewal, forests, the most important renewable resource of the East Timor lands, will lose the goods and services they provide unless this situation is overcome. The communities that live in these forests or in their vicinity will be the most affected by this problem. Understanding the structural organization of the East Timor forest flora is, therefore, critical for sustainable management of this natural resource. Thus, the main purpose of this preliminary study was to identify the differences in the floristic–structural behaviors of the woody vegetation. The study is based on data collected by the first National Forest Inventory (2008–2010), carried out in two environmentally different districts of East Timor: one drier region located to the north (Bobonaro district) and the other more humid, located in the south (Covalima district). A two-stage sampling method was employed to account for species in 923 sample stations: 480 in the Bobonaro district and 443 in the Covalima district. These data were correlated with environmental variables (altitude, distance to sea, distance to the north coast, distance to roads, and distance to urban areas) and discussed based on the floristic–structural randomness of the species frequencies. Randomness was adopted here as a parameter to quantify the distributional relationship among species with spatial heterogeneity. Results show a higher percentage of species with low frequencies and abundances for the south (lower human pressure), in contrast with the north (higher human pressure). Altitude also emerges as an environmental parameter, since this randomness floristic–structural combination decreases from lower to higher altitudes. This research provides an innovative approach to describing the structural–floristic organization of vegetation, and its correlation with environmental variables.     

The spectre of biogeographical regionalization

A biogeographical regionalization is a hierarchical system that categorizes geographical areas in terms of their biotas. I provide a general protocol to undertake biogeographical regionalizations, that consists of seven steps: (1) defining the study area; (2) assembling distributional data; (3) identifying natural areas; (4) discovering area relationships; (5) defining boundaries/transition zones; (6) regionalization and (7) area nomenclature. Natural biogeographical units are useful for people undertaking different types of analyses, like macroecologists, evolutionary biologists, systematists and conservationists. Biogeographical regionalizations may help biogeographers communicate more effectively between themselves and discover opportunities to work on common problems, contributing to the development of a truly integrative biogeography.     

Markov Chain Ontology Analysis (MCOA)

Background

Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data.

Results

In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods.

Conclusion

A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.     

Biogeographical patterns of the avifaunas of the Caribbean Basin Islands: a parsimony perspective

We analyzed the avifaunas of the Caribbean islands and nearby continental areas and their relationships using Parsimony Analysis of Endemicity (PAE), in order to assess biogeographical patterns and their concordance with geological and phylogenetic evidence. Using distributional information of birds obtained from published literature, a presence/absence matrix for 695 genera and 2026 species of land and freshwater birds was constructed and analyzed. Three different analyses were performed: for species, for genera, and for species and genera combined. In the combined analysis, the Lesser Antilles appear paraphyletic at the base of the cladogram. Then, two major clades are identified: South America (Andes, Venezuelan lowlands, Dutch West Indies and Trinidad and Tobago) and North America, including the Greater Antilles in a clade that is the sister area to Yucatan and the Central American countries nested from north to south. PAE results support Caribbean vicariant models and cladistic biogeographical hypotheses on area relationships, and show relative congruence with available phylogenetic data. Bird biogeography on the Caribbean islands appears to have been caused by both vicariance and dispersal processes. © The Willi Hennig Society 2007.     

Tree squirrels: A key to understand the historic biogeography of Mesoamerica?

A multi-taxon historical biogeography approach (Brooks Parsimony Analysis) was used to estimate relationships among the Mesoamerican lowland and highland areas and the particular biogeographic history of Mesoamerican squirrels (Sciurus, Microsciurus and Syntheosciurus species). A total of 15 lowland areas and 12 highland areas plus 41 clades comprising 240 species (45,135 records) were employed to obtain Taxon-Area Cladograms and Area Cladograms. A single most parsimonious General Area Cladogram indicated a strong vicariant relationship between Southern Mexico and the remainder of Mesoamerica, and identified several vicariant nodes (Modern Chiapanencan Volcanic Arc, Honduras’ Great Central Depression, and Nicaraguan Depression) as well as historically independent highland areas. A secondary BPA in relation with Sciurus species showed several instances of post speciation dispersal or range expansion, lack of response to vicariant events, and, possibly, lineage duplication. The results obtained suggest that Mesoamerican biotas have been subjected to several major vicariant events, but the reticulated nature of some of its areas also indicates that dispersal (post-speciation dispersal and range expansion) had been important in the diversification of the Mesoamerican biota. This trend was also observed in the particular biogeographic history of Mesoamerican tree squirrels.     

Quantitative phytogeography of the Italian Beech Forests

This paper presents a numerical analysis of the distribution patterns in Europe and adjoining regions of 242 vascular plant species occurring in the Italian beech forests. The classification of a matrix of species and of 531 Operational Geographic Units (OGUs) led to recognition of 15 different phytogeographic elements (chorotypes). The joint distribution of the species belonging to each chorotype is shown by a chorogram, which is a geographic map obtained by computer processing of the distributional data. Some of the chorograms show the main distributional centers for the beechwood flora in southern Europe: northwestern Balkan Peninsula and eastern Alps, southern Balkan Peninsula, Maritime Alps, northern Apennines, southern Apennines. Only 20% of the species are limited to narrow areas in southern Europe, and were not able to expand considerably their ranges in postglacial times. Migration from the refugia and colonization of vast areas in central and northern Europe led to intensive speciation phenomena, occurring chiefly through the formation of neopolyploid species. Several south European, narrow-ranging species, can be considered as palaeopolyploids with relict character. There is a good relationship between distribution and ecology of the chorotypes.Abbreviations OGU Operational Geographic Unit - OGS Operational Geographic Set - OCS Operational Character Set