4.5 Article

The importance of biotic interactions in species distribution models: a test of the Eltonian noise hypothesis using parrots

期刊

JOURNAL OF BIOGEOGRAPHY
卷 41, 期 3, 页码 513-523

出版社

WILEY
DOI: 10.1111/jbi.12234

关键词

AUC; Brazilian cerrado; diet; Eltonian noise hypothesis; Maxent; niche modelling; niche theory; Psittacidae; spatial resolution; variance partitioning

资金

  1. CNPq [563352/2010-8, 140121/2009-9]
  2. CAPES
  3. Division Of Environmental Biology
  4. Direct For Biological Sciences [1136586] Funding Source: National Science Foundation

向作者/读者索取更多资源

AimTo test the Eltonian noise hypothesis (ENH), that biotic interactions do not affect species distributions at large geographical scales. LocationThe Brazilian cerrado, a central South American savanna and biodiversity hotspot. MethodsWe modelled the distributions of 11 species of cerrado parrots using the software Maxent at four different spatial resolutions. We built models using abiotic variables, biotic variables (distribution of diet resources) and models combining abiotic and biotic variables. We compared model performance using the area under the curve of the receiver operating characteristic (AUC), retrieved from test data. We partitioned the variance between sets of predictors using a generalized linear model (GLM). Finally, we evaluated whether improvement in model performance (higher AUC values) in models with both abiotic and biotic variables, was related to the species' dietary niche breadth and/or spatial resolution of the models. ResultsWe found that model performance was improved in most cases by the addition of biotic variables. Our variance-partitioning approach revealed that abiotic and biotic variables contribute independently to the final model. We found no relationship between model improvement and spatial resolution. We also found no relationship between dietary niche breadth and model improvement, indicating that dietary generalist and specialist species were not differently affected by the inclusion of biotic variables in the models. Main conclusionsOur results did not support the ENH. In this study, we explicitly incorporated a biotic variable (diet resource distribution) into species distribution models (SDMs), and we showed that these variables generally improve models and have independent contributions. These results agree with previous studies that incorporated biotic variables into SDMs. Ultimately, our results indicate that SDMs performed with abiotic variables only may depict only a partial representation of the geographical distribution of a species.

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