Neftali Sillero

Dr. Neftali Sillero

Universidade do Porto
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2021 in Ecological Modelling
Verified
Journal Article
Closed access
Neftali SilleroNeftali Sillero
Neftali Sillero
Salvador Arenas-CastroSalvador Arenas-Castro
Salvador Arenas-Castro
UEUrtzi Enriquez‐Urzelai
Urtzi Enriquez‐Urzelai
CVCândida Gomes Vale
Cândida Gomes Vale
DSDiana Sousa-Guedes
Diana Sousa-Guedes
ABA.MÁrcia Barbosa
A.MÁrcia Barbosa

1 January 2014 in Amphibia-Reptilia
Verified
Journal Article
Open access
PDF file
Neftali SilleroNeftali Sillero
Neftali Sillero
JCJoão Carlos Campos
João Carlos Campos
ABAnna Bonardi
Anna Bonardi
CCClaudia Corti
Claudia Corti
RCRaymond Creemers
Raymond Creemers
MVMiguel Vences
Miguel Vences
A precise knowledge of the spatial distribution of taxa is essential for decision-making processes in land management and biodiversity conservation, both for present and under future global change scenarios. This is a key base for several scientific disciplines (e.g. macro-ecology, biogeography, evolutionary biology, spatial planning, or environmental impact assessment) that rely on species distribution maps. An atlas summarizing the distribution of European amphibians and reptiles with 50 × 50 km resolution maps based on ca. 85 000 grid records was published by the Societas Europaea Herpetologica (SEH) in 1997. Since then, more detailed species distribution maps covering large parts of Europe became available, while taxonomic progress has led to a plethora of taxonomic changes including new species descriptions. To account for these progresses, we compiled information from different data sources: published in books and websites, ongoing national atlases, personal data kindly provided to the SEH, the 1997 European Atlas, and the Global Biodiversity Information Facility (GBIF). Databases were homogenised, deleting all information except species names and coordinates, projected to the same coordinate system (WGS84) and transformed into a 50 × 50 km grid. The newly compiled database comprises more than 384 000 grid and locality records distributed across 40 countries. We calculated species richness maps as well as maps of Corrected Weighted Endemism and defined species distribution types (i.e. groups of species with similar distribution patterns) by hierarchical cluster analysis using Jaccard’s index as association measure. Our analysis serves as a preliminary step towards an interactive, dynamic and online distributed database system (NA2RE system) of the current spatial distribution of European amphibians and reptiles. The NA2RE system will serve as well to monitor potential temporal changes in their distributions. Grid maps of all species are made available along with this paper as a tool for decision-making and conservation-related studies and actions. We also identify taxonomic and geographic gaps of knowledge that need to be filled, and we highlight the need to add temporal and altitudinal data for all records, to allow tracking potential species distribution changes as well as detailed modelling of the impacts of land use and climate change on European amphibians and reptiles.

27 July 2020 in International Journal of Geographical Information Science
Verified
Journal Article
Closed access
Neftali SilleroNeftali Sillero
Neftali Sillero
ABA. Márcia Barbosa
A. Márcia Barbosa
Ecological niche models (ENMs) are widely used statistical methods to estimate various types of species niches. After lecturing several editions of introductory courses on ENMs and reviewing numerous manuscripts on this subject, we frequently faced some recurrent mistakes: 1) presence-background modelling methods, such as Maxent or ENFA, are used as if they were pseudo-absence methods; 2) spatial autocorrelation is confused with clustering of species records; 3) environmental variables are used with a higher spatial resolution than species records; 4) correlations between variables are not taken into account; 5) machine-learning models are not replicated; 6) topographical variables are calculated from unprojected coordinate systems, and; 7) environmental variables are downscaled by resampling. Some of these mistakes correspond to student misunderstandings and are corrected before publication. However, other errors can be found in published papers. We explain here why these approaches are erroneous and we propose ways to improve them.


13 July 2013 in Biological Reviews
Verified
Journal Article
Closed access
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JBJosé C. Brito
José C. Brito
RGRaquel Godinho
Raquel Godinho
Fernando Martínez-FreiríaFernando Martínez-Freiría
Fernando Martínez-Freiría
JPJuan M. Pleguezuelos
Juan M. Pleguezuelos
HRHugo Rebelo
Hugo Rebelo
SCSalvador Carranza
Salvador Carranza

6 January 2016 in PLOS ONE
Verified
Journal Article
Open access
PDF file
JBJason L. Brown
Jason L. Brown
Neftali SilleroNeftali Sillero
Neftali Sillero
FGFrank Glaw
Frank Glaw
PBParfait Bora
Parfait Bora
DVDavid R. Vieites
David R. Vieites
MVMiguel Vences
Miguel Vences
Madagascar has become a model region for testing hypotheses of species diversification and biogeography, and many studies have focused on its diverse and highly endemic herpetofauna. Here we combine species distribution models of a near-complete set of species of reptiles and amphibians known from the island with body size data and a tabulation of herpetofaunal communities from field surveys, compiled up to 2008. Though taxonomic revisions and novel distributional records arose since compilation, we are confident that the data are appropriate for inferring and comparing biogeographic patterns among these groups of organisms. We observed species richness of both amphibians and reptiles was highest in the humid rainforest biome of eastern Madagascar, but reptiles also show areas of high richness in the dry and subarid western biomes. In several amphibian subclades, especially within the Mantellidae, species richness peaks in the central eastern geographic regions while in reptiles different subclades differ distinctly in their richness centers. A high proportion of clades and subclades of both amphibians and reptiles have a peak of local endemism in the topographically and bioclimatically diverse northern geographic regions. This northern area is roughly delimited by a diagonal spanning from 15.5°S on the east coast to ca. 15.0°S on the west coast. Amphibian diversity is highest at altitudes between 800–1200 m above sea-level whereas reptiles have their highest richness at low elevations, probably reflecting the comparatively large number of species specialized to the extended low-elevation areas in the dry and subarid biomes. We found that the range sizes of both amphibians and reptiles strongly correlated with body size, and differences between the two groups are explained by the larger body sizes of reptiles. However, snakes have larger range sizes than lizards which cannot be readily explained by their larger body sizes alone. Range filling, i.e., the amount of suitable habitat occupied by a species, is less expressed in amphibians than in reptiles, possibly reflecting their lower dispersal capacity. Taxonomic composition of communities assessed by field surveys is largely explained by bioclimatic regions, with communities from the dry and especially subarid biomes distinctly differing from humid and subhumid biomes.