Strategies to optimize modeling habitat suitability of Bertholletia excelsa in the Pan-Amazonia

Author(s)

Tourne, Daiana C. M. ^[1] ; Ballester, Maria V. R. ^[1] ; James, Patrick M. A. ^[2] ; Martorano, Lucieta G. ^[3] ; Guedes, Marcelino Carneiro ^[4] ; Thomas, Evert ^[5]

Affiliation

^[1] Univ Sao Paulo, Environm Anal & Geoproc Lab, CENA, Sao Paulo - Brazil

^[2] Univ Montreal, Dept Biol Sci, Montreal, PQ - Canada

^[3] EMBRAPA Eastern Amazon, Agrometeorol Lab, Santarem - Brazil

^[4] EMBRAPA Amapa, Forest Res & Dev, Macapa - Brazil

^[5] Reg Off Amer, Biovers Int, Lima - Peru

• Document type: Journal article
• Source: ECOLOGY AND EVOLUTION; v. 9, n. 22, p. 12623-12638, NOV 2019.
• Web of Science Citations: 0

Abstract

Aim Amazon-nut (Bertholletia excelsa) is a hyperdominant and protected tree species, playing a keystone role in nutrient cycling and ecosystem service provision in Amazonia. Our main goal was to develop a robust habitat suitability model of Amazon-nut and to identify the most important predictor variables to support conservation and tree planting decisions. Localization Amazon region, South America. Methods We collected 3,325 unique Amazon-nut records and assembled >100 spatial predictor variables organized across climatic, edaphic, and geophysical categories. We compared suitability models using variables (a) selected through statistical techniques; (b) recommended by experts; and (c) integrating both approaches (a and b). We applied different spatial filtering scenarios to reduce overfitting. We additionally fine-tuned MAXENT settings to our data. The best model was selected through quantitative and qualitative assessments. Results Principal component analysis based on expert recommendations was the most appropriate method for predictor selection. Elevation, coarse soil fragments, clay, slope, and annual potential evapotranspiration were the most important predictors. Their relative contribution to the best model amounted to 75%. Filtering of the presences within a radius of 10 km displayed lowest overfitting, a satisfactory omission rate and the most symmetric distribution curve. Our findings suggest that under current environmental conditions, suitable habitat for Amazon-nut is found across 2.3 million km(2), that is, 32% of the Amazon Biome. Main conclusion The combination of statistical techniques with expert knowledge improved the quality of our suitability model. Topographic and soil variables were the most important predictors. The combination of predictor variable selection, fine-tuning of model parameters and spatial filtering was critical for the construction of a reliable habitat suitability model. (AU)

• FAPESP's process: 15/04749-1 - Modelling Amazon nut (Bertholletia excelsa Bonpl.) current and future distribution to subsidize plantations and conservation sustainable strategies
• Grantee: Daiana Carolina Monteiro Tourne
• Support Opportunities: Scholarships in Brazil - Doctorate