The impact of global climate change on the number and replacement of provisioning ecosystem services of Brazilian Cerrado plants

Ferreira, Rafael Batista; Parreira, Micael Rosa; Nabout, João Carlos

doi:10.1007/s10661-021-09529-6

Cited by 10 publications

(1 citation statement)

References 82 publications

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“…ENMs have been widely used for predicting the species' potential distribution as a species conservation tool in poorly known areas (Guisan et al, 2013). Moreover, they have been used in different research areas, such as climate change (Nabout et al, 2011;Anderson, 2013;Ruaro et al, 2019;Ferreira et al, 2021), invasive species (Jiménez-Valverde et al, 2011), disease transmission (Peterson et al, 2005), delimitation of conservation areas (Carvalho et al, 2017), the effect of habitat loss (Peterson et al, 2006), among others [see Peterson (2006) for more applications].…”

Section: Introductionmentioning

confidence: 99%

Incorporating symmetrical and asymmetrical dispersal into Ecological Niche Models in freshwater environments

2023

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Aim Ecological niche models (ENMs) are based mainly on environmental (mostly climatic) and occurrence data to predict the potential distribution of species. In freshwater habitats, species dispersal is not restricted only by physical barriers but also by the directional movement of the hydrographic network, which can be considered through spatial predictors. Here, we aim to evaluate the effect of including asymmetrical and symmetrical spatial predictors in the potential geographic distribution of a freshwater fish in the Tocantins-Araguaia River basin, Brazil. Methods For this, we built models with seven variable sets representing the climatic and spatial models, as well as their interactions. Results We found that the overall best models (higher evaluation and lower variation among modeling methods) are those built using AEM (asymmetrical dispersal [i.e., dispersal along the river flow path]), either alone or in combination with environmental variables (ENV). Moreover, the inclusion of asymmetrical dispersal variables, taking into account dispersal limitations of species, decreased the overprediction to climatically suitable but disconnected areas through rivers. Conclusions Therefore, future ENM studies, especially those using species groups with directional dispersal, should consider the inclusion of asymmetrical spatial predictors to increase the model’s accuracy and ecological reality.

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