What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods

Sillero, Neftalí

doi:10.1016/j.ecolmodel.2011.01.018

Cited by 255 publications

(195 citation statements)

References 26 publications

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“…calculation of ecological niche models; Sillero, 2011), and these were not the main goal of this compilation. We therefore did not apply any methods based on environmental niche modelling which at this level had already been carried out by Araújo, Thuiller and Pearson (2006) and Araújo et al (2008).…”

Section: Biogeographical Analysesmentioning

confidence: 99%

Updated distribution and biogeography of amphibians and reptiles of Europe

Sillero¹,

Campos²,

et al. 2014

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Abstract. 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.

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Section: Biogeographical Analysesmentioning

confidence: 99%

Updated distribution and biogeography of amphibians and reptiles of Europe

Sillero¹,

Campos²,

et al. 2014

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“…In ecological niche modelling (ENM) environmental parameters are compared within the geographical space. ENM techniques are based on statistical methods (e.g., generalized additive models (GAMs) and generalized linear models (GLMs)) and scientist-developed machine learning methods (e.g., artificial neural networks (ANNs) and maximum entropy (Maxent)) that are based on different statistical techniques [24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Predicting the Potential Distribution of Olea ferruginea in Pakistan incorporating Climate Change by Using Maxent Model

et al. 2016

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Abstract:The potential distribution of Olea ferruginea was predicted by Maxent model for present and the upcoming hypothetical (2050) climatic scenario. O. ferruginea is an economically beneficial plant species. For predicting the potential distribution of O. ferruginea in Pakistan, Worldclim variables for current and future climatic change scenarios, digital elevation model (DEM) slope, and aspects with the occurrence point were used. Pearson correlation was used to reject highly correlated variables. A total of 219 sighting points were used in the Maxent modeling. The area under curve (AUC) value was higher than 0.98. The approach used in this study is considered useful in predicting the potential distribution of O. ferruginea species, and can be an effective tool in the conservation and restoration planning for human welfare. The results show that there is a significant impact under future bioclimatic scenarios on the potential distribution of O. ferruginea in Pakistan. There is a significant decrease in the overall distribution of O. ferruginea due to loss of habitats under current distribution range, but this will be compensated by gain of habitat at higher altitudes in the future climate change scenario (habitat shift). It is recommended that the areas predicted suitable for the O. ferruginea may be used for plantation of this species while the deforested land should be restored for human welfare.

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“…Foi defendido que as abordagens mecanicistas são as que mais se aproximam do nicho da espécie e que, portanto, as abordagens correlativas deveriam fazer o uso do termo "habitat" e não "nicho" na modelagem (Kearney 2006). Na busca por artigos, as palavras-chave foram utilizadas em conjunto, pois apesar de haver fortes argumentos para a distinção conceitual (Sillero 2011, Peterson & Soberón 2012 tal procedimento é ainda recente ao tomar como referência a abrangência temporal da presente análise (2002 até 2015) e, na prática, os autores têm recorrentemente utilizado os termos como sinônimos (e.g., Fitzpatrick et al 2007, Raes 2012, Barbosa & Schneck 2015. No corpo textual foi utilizado o termo "modelagem de distribuição de espécies" (sensu Franklin 2009) ao invés de "modelagem de nicho ecológico" por ser mais inclusivo e, por consequência, retratar melhor a heterogeneidade de abordagens apresentada nos trabalhos.…”

Section: Methodsunclassified

Seleção Das Variáveis Preditoras Para Modelagem Correlativa De Distribuição De Espécies Na América Do Sul

Negrão

Löwenberg‐Neto

2018

Oecol. Aust.

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___________________________________________________________________________________________________________Resumo: Modelagem de distribuição geográfica é uma técnica utilizada para estimar a área de distribuição de espécies no espaço geográfico. A etapa de seleção das variáveis preditoras é fundamental para a construção do modelo conceitual no procedimento de modelagem correlativa. O presente estudo teve por objetivo descrever como os pesquisadores selecionaram as variáveis preditoras em seus estudos conduzidos na extensão geográfica da América do Sul. Foi realizado levantamento e revisão da literatura de estudos publicados no período de 2002 a 2014. Os artigos foram triados em duas categorias: seleção arbitrária e seleção baseada em critério. Os artigos que utilizaram critérios foram subcategorizados em quatro grupos: axiomático, biológico, estatístico ou metodológico. Do total de artigos analisados (n = 177), em 31% os autores não justificaram a seleção das variáveis. Em 24% dos artigos os autores combinaram critérios, o critério estatístico foi adotado de modo não combinado em 23% dos artigos e o biológico em 13% dos artigos. Quando os autores utilizaram algum critério, o conjunto apresentou menor número de variáveis. Os autores que adotaram o critério biológico apresentaram explicações imprecisas da relação entre as variáveis e os organismos. Pela primeira vez foi diagnosticado o procedimento de combinar critérios e este interpretado como solução para a) balancear o número de variáveis do conjunto e b) contornar o déficit de conhecimento das espécies. A maior frequência de utilização do critério estatístico, isolado e combinado, corroborou o esperado para a modelagem correlativa. Admite-se como prática adequada a seleção de variáveis utilizando princípios e análises estatísticas para a construção de conjuntos com seis a nove variáveis preditoras. A adoção plena do critério biológico necessita de estudos que descrevam com maior rigor teórico a relação entre as variáveis e as respostas ecofisiológicas dos organismos.Palavras-chave: camada matricial; espaço geográfico; fenomenologia; modelo empírico; sobreajuste. SELECTING PREDICTORS IN CORRELATIVE SPECIES DISTRIBUTION MODELING IN SOUTHAMERICA. Species distribution modelling is a technique that estimates species geographical ranges. Variable selection is a fundamental step in conceptual model formulation and in correlative modelling procedure. Herein we describe how authors selected variables in their modelling studies within the extent of the South American continent. We analysed 177 papers that were published between 2002 and 2014. For each paper, we searched for explicit information on authors' reasoning for selecting variables. We classified papers into two categories: arbitrary and criterion-based. Criterion-based papers were

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What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods

Cited by 255 publications

References 26 publications

Updated distribution and biogeography of amphibians and reptiles of Europe

Updated distribution and biogeography of amphibians and reptiles of Europe

Predicting the Potential Distribution of Olea ferruginea in Pakistan incorporating Climate Change by Using Maxent Model

Seleção Das Variáveis Preditoras Para Modelagem Correlativa De Distribuição De Espécies Na América Do Sul

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