Species Distribution Modelling: Contrasting presence-only models with plot abundance data.
Sci Rep
; 8(1): 1003, 2018 01 17.
Article
em En
| MEDLINE
| ID: mdl-29343741
ABSTRACT
Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Árvores
/
Modelos Estatísticos
/
Conservação dos Recursos Naturais
/
Dispersão Vegetal
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
America do sul
/
Brasil
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
/
UK
/
UNITED KINGDOM