Challenges and perspectives for species distribution modelling in the neotropics

Kamino, Luciana Hiromi Yoshino; Stehmann, João Renato; Amaral, Silvana; Marco, Paulo De; Rangel, Thiago F.; Siqueira, Marinez Ferreira de; Giovanni, Renato De; Hortal, Joaquín

doi:10.1098/rsbl.2011.0942

Cited by 52 publications

(53 citation statements)

References 11 publications

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“…overprediction). As the application of SDM in megadiverse Neotropics presents several challenges, especially because data on species occurrences are scarce (Kamino et al 2011), validation of model results -by experts as preferred -is extremely recommended as statistical results not always is coherent with the reality.…”

Section: Discussionmentioning

confidence: 99%

Species Distribution Modeling for Conservation Purposes

Ferraz¹,

Ferraz²,

Paula³

et al. 2012

NatCon

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Species distribution models (SDMs) can be useful for different conservation purposes. We discuss the importance of fitting spatial scale and using current records and relevant predictors aiming conservation. We choose jaguar (Panthera onca) as a target species and Brazil and Atlantic Forest biome as study areas. We tested two different extents (continent and biome) and resolutions (~4 Km and ~1 Km) in Maxent with 186 records and 11 predictors (bioclimatic, elevation, land-use and landscape structure). All models presented satisfactory AUC values (>0.70) and low omission errors (<23%). SDMs were scale-sensitive as the use of reduced extent implied in significant gains to model performance generating more constrained and real predictive distribution maps. Continental-scale models performed poorly in predicting potential current jaguar distribution, but they reached the historic distribution. Specificity increased significantly from coarse to finer-scale models due to the reduction of overprediction. The variability of environmental space (E-space) differed for most of climatic variables between continental and biome-scale and the representation of the E-space by predictors differed significantly (t = 2.42, g.l.= 9, P < 0.05). Refining spatial scale, incorporating landscape variables and improving the quality of biological data are essential for improving model prediction for conservation purposes.

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Section: Discussionmentioning

confidence: 99%

Species Distribution Modeling for Conservation Purposes

Ferraz¹,

Ferraz²,

Paula³

et al. 2012

NatCon

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“…Therefore, the wide availability of species occurrence data, environmental data with different resolutions and computational tools have contributed to the widespread use of niche models. In fact, some papers highlights the importance of niche models in macroecological studies (Kerr et al 2007), including those defining guidelines for research in particular regions (i.e., the Neotropical regions -see Kamino et al 2012), discussing the implications for establishing conservation strategies (Araújo et al 2011), aspects of biological invasions (Bradley et al 2010) and the spread of diseases (Lafferty 2009). …”

Section: Publications Trends and Biasesmentioning

confidence: 99%

Trends and Biases in Global Climate Change Literature

Nabout¹,

Carvalho²,

Prado³

et al. 2012

Nat. Conserv.

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The purpose of this study is to conduct a scientometric analysis of the global climate change (GCC) literature to identify the patterns, trends and biases in this research field. Data were obtained using the Thomson ISI database. A total of 5,444 articles on GCC were recorded, showing a temporal increase in the number of articles (r = 0.84; P < 0.0001). Most the articles look at the impact of climate change on geophysical variables, humans and vegetation. Few studies look at fungi, amphibians or reptiles (H = 24.6; P < 0.0001, N = 27). Principal component analysis revealed a temporal difference in the keywords associated with each article. In the first years we observed that the most frequent keywords indicated worry about the main causes of global climate change, but this shifted in more recent years towards keywords indicating concern with the effects of climate change on biodiversity. We argue that this scientometric study can help guide future climate change research and contribute to our understanding of several poorly studied areas.

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“…The main criteria used to evaluate the extinction risk of species have been trends in population size and/or geographical distribution range (Paglia & Fonseca 2009). However, these data are incomplete for most Neotropical species due to the small number of data points and/or spatially biased records, which makes it difficult to decide on the conservation status of species (Kamino et al 2012).…”

Section: Introductionmentioning

confidence: 99%

“…In this scenario, species with very few occurrences in combination with species distribution model (SDMs) methods may be useful for providing a description of the areas climatically similar to the recorded presences, allowing the planning of new field surveys (Kamino et al 2012). These methods are an important tool to make predictions about distribution of poorly known species which are, probably, under risk of extinction (Raxworthy et al 2003).…”

Section: Introductionmentioning

confidence: 99%

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Reassessment of the extinction risk of endemic species in the Neotropics: How can modelling tools help us?

Kamino¹,

Siqueira²,

Sánchez‐Tapia³

et al. 2012

NatCon

Self Cite

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Occurrence data on geographic distribution for most endemic Neotropical plants are scarce and spatially biased, which interferes with decisions on their conservation status. In this study we present a three-step approach applying: 1) Euclidean Environmental Distance models to search for unknown populations; 2) MaxEnt incorporating additional presence data to produce forecasts of the potential distribution and 3) coupling of convex hull methods with SDM. We studied Petunia mantiqueirensis, an Atlantic Forest endemic species. This approach enabled us to obtain new presence points, and to improve species distribution models. Finally, we identified and excluded environmental unsuitable areas inside the extent of occurrence, allowing us to reassess the conservation status of the species. These recommendations are important to crucial to establish, in a more assertive way, the extent of occurrence and area of occupancy of the species to determine proper strategies for conservation.

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Challenges and perspectives for species distribution modelling in the neotropics

Cited by 52 publications

References 11 publications

Species Distribution Modeling for Conservation Purposes

Species Distribution Modeling for Conservation Purposes

Trends and Biases in Global Climate Change Literature

Reassessment of the extinction risk of endemic species in the Neotropics: How can modelling tools help us?

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