Modelos predictivos de diversidad: aplicaión al estudio de la riqueza de araneidos y tomísidos (arachnida, araneae, araneidae & thomisidae) en la Comunidad de Madrid y a la predicción de la distribución de macrothele calpeiana (arachnida, araneae, hexathelidae) en la Península Ibérica

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología. Fecha de lectura 13-09-200

Species distribution models predict range expansion better than chance but not better than a simple dispersal model

The evaluation of species distribution models (SDMs) is a crucial step; usually, a random subsample of data is used to test prediction capacity. This procedure, called cross-validation, has been recently shown to overestimate SDMs performance due to spatial autocorrelation. In the case of expanding species, there exists the possibility to test the predictions with non-random geographically structured data, i.e., a new data set which corresponds to the last occupied localities. The aim of this study was to evaluate the capacity of SDMs to predict the range expansion pattern of six free-living deer species in Great Britain and to assess whether SDMs perform better than a simple dispersal model - a null model that assumes no environmental control in the expansion process. Distribution data for the species prior to 1972 were used to train the SDMs (ENFA, MAXENT, logistic regression and an ensemble model) in order to obtain suitability maps. Additionally, the geographical distance to the localities occupied in 1972 was considered a proxy of the probability that a certain locality has to be occupied during an expansion process considering only dispersal (GD model). Subsequently, we analysed whether the species increased their ranges between 1972 and 2006 according to the estimated suitability patterns and whether or not SDMs predictions outperformed GD predictions. SDMs showed a high discrimination capacity in the training data, with the ensemble models performing the best and ENFA models the worst. SDMs predictions also worked better than chance in classifying new occupied localities, although differences among techniques disappeared and the predictions showed no difference with respect to GD. Spatial autocorrelation of both the environmental predictors and the expansion process may explain these results which illustrate that GD is a much more parsimonious model than any of the SDMs and may thus be preferable both for prediction and explanation. Overestimation of SDMs performance and usefulness may be a common fact.M.R.-R. was supported by project POII10-0076-4195 of JCCM, A.J.-V. by the MEC Juan de la Cierva Program and P.A. was funded from the SFRH/BPD/90320/2012 post-doctoral grant by Portuguese Fundação para a Ciência e a Tecnologia (FCT) and European Social Fund.Peer Reviewe

Delimiting the geographical background in species distribution modelling

[Aim]: The extent of the study area (geographical background, GB) can strongly affect the results of species distribution models (SDMs), but as yet we lack objective and practicable criteria for delimiting the appropriate GB. We propose an approach to this problem using trend surface analysis (TSA) and provide an assessment of the effects of varying GB extent on the performance of SDMs for four species. [Location]: Mainland Spain. [Methods]: Using data for four well known wild ungulate species and different GBs delimited with a TSA, we assessed the effects of GB extent on the predictive performance of SDMs: specifically on model calibration (Miller's statistic) and discrimination (area under the curve of the receiver operating characteristic plot, AUC; sensitivity and specificity), and on the tendency of the models to predict environmental potential when they are projected beyond their training area. [Results]: In the training area, discrimination significantly increased and calibration decreased as the GB was enlarged. In contrast, as GB was enlarged, both discriminatory power and calibration decreased when assessed in the core area of the species distributions. When models trained using small GBs were projected beyond their training area, they showed a tendency to predict higher environmental potential for the species than those models trained using large GBs. [Main conclusions]: By restricting GB extent using a geographical criterion, model performance in the core area of the species distribution can be significantly improved. Large GBs make models demonstrate high discriminatory power but are barely informative. By delimiting GB using a geographical criterion, the effect of historical events on model parameterization may be reduced. Thus purely environmental models are obtained that, when projected onto a new scenario, depict the potential distribution of the species. We therefore recommend the use of TSA in geographically delimiting the GB for use in SDMs.P.A. and A.J.-V. were supported by the Juan de la Cierva research program awarded by the Ministerio de Ciencia e Innovación – Fondo Social Europeo, and partly by the project CGL2009-11316/BOS – Fondos FEDER. P.A. is in Portugal thanks to a José Castillejo fellowship (2010–11) granted by the Ministerio de Ciencia e Innovación.Peer Reviewe

ENVIRONMENTAL CORRELATION STRUCTURE AND ECOLOGICAL NICHE MODEL PROJECTIONS

Non

Parapatric species and the implications for climate change studies: a case study on hares in Europe

Parapatry is a biogeographical term used to refer to organisms whose ranges do not overlap, but are immediately adjacent to each other; they only co-occur - if at all - in a narrow contact zone. Often there are no environmental barriers in the contact zones, hence competitive interaction is usually advocated as the factor that modulates species distribution ranges. Even though the effects of climate change on species distribution have been widely studied, few studies have explored these effects on the biogeographical relationships between closely related, parapatric, species. We modelled environmental favourability for three parapatric hare species in Europe - Lepus granatensis, L. europaeus and L. timidus - using ecogeographical variables and projected the models into the future according to the IPCC A2 emissions scenario. Favourabilities for present and future scenarios were combined using fuzzy logic with the following aims: (i) to determine the biogeographical relationships between hare species in parapatry, that is L. granatensis/L. europaeus and L. europaeus/L. timidus and (ii) to assess the effects of climate change on each species as well as on their interspecific interactions. In their contact area L. granatensis achieved higher favourability values than L. europaeus, suggesting that if both species have a similar population status, the former species may have some advantages over the latter if competitive relationships are established. Climate change had the most striking effect on the distribution of L. timidus, especially when interspecific interactions with L. europaeus were taken into account, which may compromise the co-existence of L. timidus. The results of this study are relevant not only for understanding the distribution patterns of the hares studied and the effects of climate change on these patterns, but also for improving the general application of species distribution models to the prediction of the effects of climate change on biodiversity.We are grateful to A.M. Barbosa for her ever-useful advice. P. A. and A. J.-V. were supported by the Juan de la Cierva research program awarded by the Ministerio de Ciencia e Innovación–Fondo Social Europeo, and partially by the project CGL2009-11316/BOS from the Spanish Government and FEDER. P. A. is a current holder of the Jose Castillejo fellowship (2010–2011) in Portugal awardedby the Ministerio de Ciencia e Innovación. J. M.-F. has a post-doctoral grant funded by FCT and the European Social Fund (SFRH/BPD/43264/2008). This work was partially funded bythe research projects PTDC/BIA-EVF/111931/2009 and PTDC/BIA-EVF/115069/2009 funded by FCT and FEDER.Peer Reviewe

Discrimination capacity in species distribution models depends on the representativeness of the environmental domain

[Aim]: When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time, we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models. [Innovation]: In this paper we corroborate that, under a uniform distribution of the estimated probability of presence, a well-calibrated model will not attain high discrimination power and the value of the area under the curve will be 0.83. Under non-uniform distributions of the probability of presence, simulations show that a well-calibrated model can attain a broad range of discrimination values. These results illustrate that discrimination is a context-dependent property, i.e. it gives information about the performance of a certain algorithm in a certain data population. [Main conclusions]: In species distribution modelling, the discrimination capacity of a model is only meaningful for a certain species in a given geographic area and temporal snapshot. This is because the representativeness of the environmental domain changes with the geographical and temporal context, which unavoidably entails changes in the distribution of the probability of presence. Comparative studies that intend to generalize their results only based on the discrimination capacity of models may not be broadly extrapolated. Assessment of calibration is especially recommended when the models are intended to be transferred in time or space.The study was partially supported by projects CGL2009-11316/BOS-FEDER and CGL2011-25544. A.J.-V. was supported by the MEC Juan de la Cierva Program. P.A. was supported by the Vicerrectorado de Investigación of the University of Málaga. A.M.B. was supported by a post-doctoral fellowship from Fundação para a Ciência e aTecnologia (Portugal), co-financed by the European Social Fund. The ‘Rui Nabeiro’ Biodiversity Chair receives funding from Delta Cafés.Peer Reviewe

El relicto glacial Leistus (Pogonophorus) puncticeps Fairmaire & Laboulbène, 1854 (Coleoptera, Carabidae): nuevos datos sobre distribución, autoecología y presencia en el Medio Subterráneo Superficial (MSS)

Over the last three decades, intensive sampling of the MSS in the Iberian Peninsula has revealed new records of Leistus (Pogonophorus) puncticeps Fairmaire & Laboulbène, 1854 in previously unknown areas. These new records extend the species geographic range towards southern Mediterranean localities, showing a discontinu­ous distribution pattern across the eastern third of the Iberian Peninsula. Also, some slight variability in the shape of the apical lamina of the edeago is revealed. Abrupt landscape, especially in stony slopes, arises as a favorable habitat for the species. In general, the new localities for L. (P.) puncticeps have low and torrential precipitation, an average rainfall of around 600-700 mm, and remarkable thermal amplitude. The species is collected for the first time in the Mesovoid Sallow Substratum (MSS) using subterranean sampling devices (SSD). The pres­ence of this species in this hypogean habitat across several iberian areas (Sierra del Moncayo, mountains of the north of Alicante province and Sierra de María) indicates its (sub)troglophile condition. The new records, in addition to previously available data, suggest the same evolutionary history for L. (P.) puncticeps as for Leistus (Pogonophorus) montanus Stephens, 1827 and Leistus (Pogonophorus) parvicollis Chaudoir, 1869, being the three species glacial relicts as a result of vicariant speciation. The environmental changes that occurred during the postglacial time period could explain the discontinuous distribution that L. (P.) puncticeps shows at present and its tendency to occupy the MSS.Numerosos muestreos realizados por el territorio peninsular, a lo largo de estas tres últimas décadas, han deparado el hallazgo de Leistus (Pogonophorus) puncticeps Fairmaire & Laboulbène, 1854 en áreas geográfi­cas en las que se desconocía su presencia hasta la fecha. Las nuevas citas amplían la distribución ibérica de la especie hacia enclaves mediterráneos meridionales, perfilando un patrón de distribución discontinuo por el tercio oriental. Al mismo tiempo, estos hallazgos revelan cierta variabilidad, muy leve, en la forma de la lámina apical del edeago. Por otro lado, se confirman los parajes quebrados y abruptos como enclaves potencialmente favorables para la supervivencia de esta especie, especialmente si disponen de laderas pedregosas. En general, las nuevas localidades en donde se ha hallado L. (P.) puncticeps, cuentan con precipitación escasa y torrencial, una pluvio­sidad media que ronda los 600-700 mm, y una notable amplitud térmica. Como novedad, y utilizando Estaciones de Muestreo Subterráneo (EMS), se ha colectado en el Medio Subterráneo Superficial (MSS). El hallazgo de esta especie en este singular medio hipogeo y en diversos enclaves ibéricos (Sierra del Moncayo, formaciones montañosas del norte de la provincia de Alicante y Sierra de María), pone de manifiesto su tendencia troglófila, y más probablemente de tipo subtroglófila. Los nuevos hallazgos, sumados a los ya conocidos, sugieren que L. (P.) puncticeps ha seguido la misma historia evolutiva que Leistus (Pogonophorus) montanus Stephens, 1827 y Leistus (Pogonophorus) parvicollis Chaudoir, 1869, constituyendo una triada de relictos glaciales, resultado de un proceso de especiación por vicarianza. Los cambios acaecidos en el período postglacial explicarían la distribución discontinua que muestra en la actualidad L. (P.) puncticeps, y su tendencia a explorar, en estos enclaves, el MSS

rangemap: An R Package to Explore Species' Geographic Ranges

Data exploration is a critical step in understanding patterns and biases in information about species’ geographic distributions. We present rangemap, an R package that implements tools to explore species’ ranges based on simple analyses and visualizations. The rangemap package uses species occurrence coordinates, spatial polygons, and raster layers as input data. Its analysis tools help to generate simple spatial polygons summarizing ranges based on distinct approaches, including spatial buffers, convex and concave (alpha) hulls, trend-surface analysis, and raster reclassification. Visualization tools included in the package help to produce simple, high-quality representations of occurrence data and figures summarizing resulting ranges in geographic and environmental spaces. Functions that create ranges also allow generating extents of occurrence (using convex hulls) and areas of occupancy according to IUCN criteria. A broad community of researchers and students could find in rangemap an interesting means by which to explore species’ geographic distributions

rangemap: An R Package to Explore Species' Geographic Ranges

Data exploration is a critical step in understanding patterns and biases in information about species’ geographic distributions. We present rangemap, an R package that implements tools to explore species’ ranges based on simple analyses and visualizations. The rangemap package uses species occurrence coordinates, spatial polygons, and raster layers as input data. Its analysis tools help to generate simple spatial polygons summarizing ranges based on distinct approaches, including spatial buffers, convex and concave (alpha) hulls, trend-surface analysis, and raster reclassification. Visualization tools included in the package help to produce simple, high-quality representations of occurrence data and figures summarizing resulting ranges in geographic and environmental spaces. Functions that create ranges also allow generating extents of occurrence (using convex hulls) and areas of occupancy according to IUCN criteria. A broad community of researchers and students could find in rangemap an interesting means by which to explore species’ geographic distributions