Anisotropic (direction-dependent) long-distance dispersal (LDD) by wind has been invoked to explain the strong floristic affinities shared among landmasses in the Southern Hemisphere. Its contribution has not yet been systematically tested because of the previous lack of global data on winds. We used global winds coverage from the National Aeronautics and Space Administration SeaWinds scatterometer to test whether floristic similarities of Southern Hemisphere moss, liverwort, lichen, and pteridophyte floras conform better with (i) the anisotropic LDD hypothesis, which predicts that connection by "wind highways" increases floristic similarities, or (ii) a direction-independent LDD hypothesis, which predicts that floristic similarities among sites increase with geographic proximity. We found a stronger correlation of floristic similarities with wind connectivity than with geographic proximities, which supports the idea that wind is a dispersal vehicle for many organisms in the Southern Hemisphere.

Aim  The presence‐only data stored in natural history collections is the most important source of information available regarding the distribution of organisms. These data and profile techniques can be used to generate species distribution models (SDMs), but pseudo‐absences must be generated to use group discriminative techniques. In this study, we evaluated whether the SDMs generated with pseudo‐absences are reliable and also if there are differences in the results obtained with profile and group discriminative techniques.Location  Ecuador, South America.Methods  The SDMs were generated with a training data set for each of the five species of Anthurium and six different methods: two profile techniques (BIOCLIM and Gower’s distance index), three group discriminative techniques [logistic multiple regression (LMR), multivariate adaptative regression splines (MARS) and Maxent] and a mixed modelling approach genetic algorithm for rule‐set production (GARP), which employs a combination of profile and group discriminative techniques and generates its own pseudo‐absences. For LMR, MARS and Maxent, three types of absences were generated: (1) random pseudo‐absences in equal number to presences and excluding a buffer area around presences (except for Maxent, which assumes that this background sample includes presences), (2) a large number (10,000) of random pseudo‐absences, also excluding a buffer area around each presence and (3) ‘target‐group absences’ (TGA), consisting of sites where other species of the group have been collected by the specialist, but not the species being modelled. To compare the predictive performance of the SDMs, the area under the curve statistic was calculated using an independent testing data set for each species.Results  MARS, Maxent and LMR produce better results than the profile techniques. The models created with TGA are generally more accurate than those generated with pseudo‐absences.Main conclusions  The advantages and disadvantages of different options for using pseudo‐absences and TGA with profile and group discriminative modelling techniques are explained and recommendations are made for the future.

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Global wind patterns influence dispersal and migration processes of aerial organisms, propagules and particles, which ultimately could determine the dynamics of colonizations, invasions or spread of pathogens. However, studying how wind-mediated movements actually happen has been hampered so far by the lack of high resolution global wind data as well as the impossibility to track aerial movements. Using concurrent data on winds and actual pathways of a tracked seabird, here we show that oceanic winds define spatiotemporal pathways and barriers for large-scale aerial movements. We obtained wind data from NASA SeaWinds scatterometer to calculate wind cost (impedance) models reflecting the resistance to the aerial movement near the ocean surface. We also tracked the movements of a model organism, the Cory's shearwater (Calonectris diomedea), a pelagic bird known to perform long distance migrations. Cost models revealed that distant areas can be connected through “wind highways” that do not match the shortest great circle routes. Bird routes closely followed the low-cost “wind-highways” linking breeding and wintering areas. In addition, we found that a potential barrier, the near surface westerlies in the Atlantic sector of the Intertropical Convergence Zone (ITCZ), temporally hindered meridional trans-equatorial movements. Once the westerlies vanished, birds crossed the ITCZ to their winter quarters. This study provides a novel approach to investigate wind-mediated movements in oceanic environments and shows that large-scale migration and dispersal processes over the oceans can be largely driven by spatiotemporal wind patterns.

RESUMENEn los últimos años se ha generalizado una nueva herramienta que permite analizar objetivamente los patrones espaciales de presencia de organismos: los modelos de distribución de especies. Estos modelos se basan en procedimientos estadísticos y cartográficos que partiendo de datos reales de presencia permiten inferir zonas potencialmente idóneas en función de sus características ambientales. Los datos de colecciones de historia natural pueden ser utilizados para este fin adquiriendo así una nueva utilidad. Los modelos han evolucionado desde su aplicación a especies aisladas hasta análisis de cientos o miles de taxones para combinarlos en el análisis de la biodiversidad y riqueza específica. En este trabajo se hace una revisión sobre la variedad de métodos utilizables, sus potencialidades e inconvenientes y los factores limitantes que influyen en la interpretación de lo que los modelos de distribución significan.Palabras clave: modelización ecológica, modelos de distribución de especies, revisión. ABSTRACTIn the last years a new tool has become widely used in ecological studies: species distribution models. These models analyze the spatial patterns of presence of organisms objectively, by means of statistical and cartographic procedures based on real data. They infer the presence of potentially suitable areas according to their environmental characteristics. Data stored in natural history collections can be used for this purpose, which gives new opportunities to use to these types of data. The models have evolved from the analysis of single species to the study of hundreds or thousands of taxa which are combined for the assessment of biodiversity and species richness. In this paper we review the variety of methods used, their potential and weaknesses, and the limiting factors that influence the interpretation of species distribution models. Key words: ecological modeling, revision, species distribution models. INTRODUCCIÓNLa generalización de los Sistemas de Información Geográfica y el desarrollo de técnicas estadísticas aplicadas ha permitido en los últimos años la expansión de herramientas para el análisis de los patrones espaciales de presencia y ausencia de especies: los modelos de distribución de especies (Franklin 1995, Guisan & Zimmermann 2000, Rushton et al. 2004, Foody 2008, Swenson 2008. Los modelos de distribución de especies están en pleno desarrollo y expansión con nuevos métodos y estrategias para el tratamiento e interpretación (Wilson et al. 2005, Elith et al. 2006, Ferrier & Guisan 2006, Mateo 2008. Como consecuencia, se han acumulado abundantes artículos con contribuciones metodológicas y teóricas significativas para la modelización de la distribución de especies.Este trabajo sintetiza la información disponible en la actualidad de una forma ordenada. Para ello se ha partido de las principales revisiones publicadas hasta la fecha (

Logistic Multiple Regression, Principal Component Regression and Classification and Regression Tree Analysis (CART), commonly used in ecological modelling using GIS, are compared with a relatively new statistical technique, Multivariate Adaptive Regression Splines (MARS), to test their accuracy, reliability, implementation within GIS and ease of use. All were applied to the same two data sets, covering a wide range of conditions common in predictive modelling, namely geographical range, scale, nature of the predictors and sampling method.We ran two series of analyses to verify if model validation by an independent data set was required or cross-validation on a learning data set sufficed. Results show that validation by independent data sets is needed. Model accuracy was evaluated using the area under Receiver Operating Characteristics curve (AUC). This measure was used because it summarizes performance across all possible thresholds, and is independent of balance between classes.MARS and Regression Tree Analysis achieved the best prediction success, although the CART model was difficult to use for cartographic purposes due to the high model complexity.

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.

To test the potential effects of winds on the migratory detours of shearwaters, transequatorial migrations of 3 shearwaters, the Manx Puffinus puffinus, the Cory's Calonectris diomedea, and the Cape Verde C. edwardsii shearwaters were tracked using geolocators. Concurrent data on the direction and strength of winds were obtained from the NASA SeaWinds scatterometer to calculate daily impedance models reflecting the resistance of sea surface winds to the shearwater movements. From these models we estimated relative wind-mediated costs for the observed synthesis pathway obtained from tracked birds, for the shortest distance pathway and for other simulated alternative pathways for every day of the migration period. We also estimated daily trajectories of the minimum cost pathway and compared distance and relative costs of all pathways. Shearwaters followed 26 to 52% longer pathways than the shortest distance path. In general, estimated wind-mediated costs of both observed synthesis and simulated alternative pathways were strongly dependent on the date of departure. Costs of observed synthesis pathways were about 15% greater than the synthesis pathway with the minimum cost, but, in the Cory's and the Cape Verde shearwaters, these pathways were on average 15 to 20% shorter in distance, suggesting the extra costs of the observed pathways are compensated by saving about 2 travelling days. In Manx shearwaters, however, the distance of the observed synthesis pathway was 25% longer than that of the lowest cost synthesis pathway, probably because birds avoided shorter but potentially more turbulent pathways. Our results suggest that winds are a major determinant of the migratory routes of seabirds.