Prediction of geographic distribution and ecological niche modeling of açaí palm trees in the Amazon

Marques, Maria José; Bezerra, Caroline de Souza; Tomaz, Jennifer Souza; Lopes, Ricardo; Wrege, Marcos Silveira; Aguiar, Ananda Virginia de; Ramos, Santiago Linorio Ferreyra; Meneses, Carlos Henrique Salvino Gadêlha; Fraxe, Therezinha de Jesus Pinto; Lopes, Maria Teresa Gomes

doi:10.1590/1983-40632024v5478108

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Research Article • Pesqui. Agropecu. Trop. 54 • 2024 • https://doi.org/10.1590/1983-40632024v5478108 copy

Prediction of geographic distribution and ecological niche modeling of açaí palm trees in the Amazon

Predição de distribuição geográfica e modelagem de nicho ecológico de açaizeiros na Amazônia

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Euterpe precatória Mart. (açaí-do-amazonas) and Euterpe oleracea Mart. (açaí-do-pará) are palm trees of socioeconomic importance to Brazil, and fruit demand has increased due to its nutritional characteristics. This study aimed to evaluate the effect of global climate change on the current geographic distribution of E. precatória and E. oleracea and in future climate scenarios using the ecological niche modeling in the scope of Brazilian territories. The modelings used 28 environmental variables, including climatic and edaphic data. The current distribution was verified for the reference period (2009-2019) and future projections were evaluated in two scenarios (Shared Socioeconomic Pathways - SSP): SSP 245 (less pessimistic) and SSP 585 (more pessimistic), in the time interval of 2061-2080. All algorithms presented satisfactory evaluation indexes. Euterpe precatória has a predominant geographic distribution in the Amazon domain, while E. oleracea has potential occurrence in three Brazilian phytogeographic domains: Amazon, Cerrado and Atlantic Forest. Euterpe oleracea showed to be more sensitive to climate change in both scenarios, while E. precatoria was more resilient up to a certain level of temperature increase (SSP 245).

KEYWORDS:
Euterpe spp.; mudanças climáticas; modelagem de distribuição de espécies

Variables	Principal component (PC)
Variables	PC1	PC2	PC3	PC4	PC5	PC6
Bio1	−0.2707	−0.2257	0.1302	−0.0462	0.0612	0.0022
Bio2	0.1767	−0.2413	0.1159	0.4889	−0.1291	0.5284
Bio3	−0.2378	−0.0120	−0.3183	0.1014	0.2300	0.5198
Bio4	0.2489	0.0078	0.3866	−0.0643	−0.2282	−0.0908
Bio5	−0.1927	−0.3193	0.3409	−0.0384	−0.1331	0.0694
Bio6	−0.2940	−0.1193	−0.0036	−0.1567	0.0890	−0.0169
Bio7	0.2492	−0.1248	0.3247	0.1931	−0.2547	0.0897
Bio8	−0.2334	−0.2547	0.2325	0.0629	0.1127	−0.0032
Bio9	−0.2765	−0.1545	−0.0162	−0.1722	0.0048	0.0252
Bio10	−0.2304	−0.2633	0.3052	−0,1006	−0.0318	−0.0260
Bio11	−0.2858	−0.1827	0.0033	−0.0302	0.1026	0.0274
Bio12	−0.2630	0.2206	0.0386	0.1832	−0.1994	−0.0609
Bio13	−0.2692	0.0792	−0.1161	0.2335	−0.3329	−0.2086
Bio14	−0.1442	0.3955	0.2416	0.0341	0.1130	0.3041
Bio15	0.0331	−0.3381	−0.4061	0.3321	−0.1420	0.0019
Bio16	−0.2698	0.0876	−0.1038	0.2389	−0.3300	−0.2091
Bio17	−0.1551	0.3949	0.2323	0.0355	0.0830	0.2766
Bio18	−0.1602	0.1883	0.2022	0.5774	0.3222	−0.3318
Bio19	−0.1991	0.2068	−0.0761	−0.2126	−0.5974	0.2389

Algorithms	Euterpe precatoria					Euterpe oleracea
Algorithms	BIO	DOM	MXS	RDF	SVM	BIO	DOM	MXS	RDF	SVM
AUC	0.93 ± 0.06	0.94 ± 0.02	0.97 ± 0.02	0.98 ± 0.01	0.98 ± 0.01	0.93 ± 0.05	0.98 ± 0.01	0.96 ± 0.02	0.99 ± 0.01	0.99 ± 0.01
Kappa	0.86 ± 0.13	0.75 ± 0.05	0.89 ± 0.04	0.91 ± 0.07	0.90 ± 0.02	0.86 ± 0.10	0.92 ± 0.05	0.81 ± 0.06	0.95 ± 0.06	0.94 ± 0.03
TSS	0.86 ± 0.13	0.75 ± 0.05	0.89 ± 0.04	0.91 ± 0.07	0.90 ± 0.02	0.86 ± 0.10	0.92 ± 0.05	0.81 ± 0.06	0.95 ± 0.06	0.94 ± 0.03
Jaccard	0.86 ± 0.13	0.80 ± 0.03	0.89 ± 0.03	0.92 ± 0.06	0.90 ± 0.02	0.86 ± 0.10	0.92 ± 0.05	0.83 ± 0.05	0.96 ± 0.05	0.94 ± 0.02
Sorensen	0.92 ± 0.08	0.89 ± 0.02	0.94 ± 0.02	0.96 ± 0.03	0.95 ± 0.01	0.92 ± 0.06	0.96 ± 0.03	0.91 ± 0.03	0.98 ± 0.01	0.97 ± 0.03

Species	Phytogeographic domain	Current period (km²)	SSP 245 (km²)	Area (%)	SSP 585 (km²)	Area (%)
Euterpe precatoria	Amazon	3,309,481.70	3,787,889.97	14.46	2,701,197.58	−18.38
	Caatinga	2,645.28	6,598.89	149.46	1,081.16	−59.13
	Cerrado	401,085.95	1,054,647.43	162,95	419,967.57	4.71
	Atlantic Forest	19,831.29	48,937.76	146.77	16,245.24	−18.08
	Pampa	0	0	0	0	0
	Pantanal	9,073.37	83.95	−99.07	143.96	−98.41
Euterpe oleracea	Amazônia	3,705,476.75	3,646,971.11	−1.58	3,010,012.91	−18.77
	Caatinga	86,975.52	28,476.61	−67.26	9,098.33	−89.54
	Cerrado	1,558,739.37	1,039,383.80	−33.32	356,964.10	−77.10
	Atlantic Forest	479,323.27	502,059.34	4.74	337,755.01	−29.54
	Pampa	0	0	0	0	0
	Pantanal	145,735.04	78,559.34	−46.09	0	−100.00

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[TFN1] Bio1: average annual temperature (°C); Bio2: average monthly daily temperature variation (°C); Bio3: isothermality; Bio4: seasonality of temperature; Bio5: maximum temperature in the hottest month (°C); Bio6: minimum temperature in the coldest month (°C); Bio7: annual temperature change (°C); Bio8: average temperature in the wettest quarter (°C); Bio9: average temperature in the driest quarter (°C); Bio10: average temperature in the hottest quarter (°C); Bio11: average temperature in the coldest quarter (°C); Bio12: rainfall accumulated in the year (mm); Bio13: rainfall accumulated in the wettest month (mm); Bio14: rainfall accumulated in the driest month (mm); Bio15: rainfall seasonality; Bio16: rainfall accumulated in the wettest quarter (mm); Bio17: rainfall accumulated in the driest quarter (mm); Bio18: rainfall accumulated in the hottest quarter (mm); Bio19: rainfall accumulated in the coldest quarter (mm).