Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil

doi:10.3832/ifor4104-016

Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil

Héveli Kalini Viana Santos⁽¹⁾, Robson Borges De Lima⁽²⁾ , Rafael Lucas Figueiredo De Souza⁽³⁾, Domingos Cardoso⁽⁴⁾, Peter W Moonlight⁽⁵⁾, Thaine Teixeira Silva⁽¹⁾, Cinthia Pereira De Oliveira⁽²⁾, Francisco Tarcísio Alves Júnior⁽²⁾, Elmar Veenendaal⁽⁶⁾, Luciano Paganucci De Queiroz⁽⁷⁾, Priscyla MS Rodrigues⁽⁸⁾, Rubens Manoel Dos Santos⁽⁹⁾, Tiina Sarkinen⁽¹⁰⁾, Alessandro De Paula⁽¹⁾, Patrícia Anjos Bittencourt Barreto-Garcia⁽¹⁾, Toby Pennington⁽¹¹⁾, Oliver L Phillips⁽¹²⁾

iForest - Biogeosciences and Forestry, Volume 16, Issue 2, Pages 116-126 (2023)
doi: https://doi.org/10.3832/ifor4104-016
Published: Apr 17, 2023 - Copyright © 2023 SISEF

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Climate change is being intensified by anthropogenic emission of greenhouse gasses, highlighting the value of forests for carbon dioxide storing carbon in their biomass. Seasonally dry tropical forests are a neglected, threatened, but potentially critical biome for helping mitigate climate change. In South America, knowing the amount and distribution of carbon in Caatinga seasonally dry vegetation is essential to understand its contribution to the global carbon cycle and subsequently design a strategic plan for its conservation. The present study aimed to model and map the spatial distribution of the potential forest biomass stock across 32 forest fragments of Caatinga, in the state of Bahia, Brazil, using regression kriging and Inverse Square of Distance techniques, building from point measurements of vegetation biomass made on-the-ground in ecological plots. First, a model for estimating biomass was fitted as a function of environmental variables to apply regression kriging, and then applied to the maps of the selected components. Elevation, temperature, and precipitation explained 46% of the biomass variations in the Caatinga. The model residuals showed strong spatial dependence and were mapped based on geostatistical criteria, selecting the spherical semivariogram model for interpolation by ordinary kriging. Biomass was also mapped by the Inverse Square of Distance approach. The quality of the regression model suggests that there is good potential for estimating biomass here from environmental variables. The regression kriging showed greater detail in the spatial distribution and revealed a spatial trend of increasing biomass from the north to south of the domain. Additional studies with greater sampling intensity and the use of other explanatory variables are suggested to improve the model, as well as to maximize the technique’s ability to capture the actual biomass behavior in this newly studied seasonally dry ecosystem.

Keywords

Geostatistics, Regression Kriging, Spatial Analysis, Forest Inventory

Authors’ address

(1)

0000-0003-1623-906X
0000-0001-6082-371X
0000-0003-3676-3846
0000-0002-8559-2927
Universidade Estadual do Sudoeste da Bahia, Departamento de Ciências Florestais, 45031-900 Vitória da Conquista, BA (Brazil)

(2)

0000-0001-5915-4045

Universidade do Estado do Amapá, Departamento de Engenharia Florestal, 68900-070 Macapá, AP (Brazil)

(3)

0000-0002-1328-057X
Universidade de São Paulo, Escola Superior de Agricultura Luiz de Queiroz, 13418-900, Piracicaba, SP (Brazil)

(4)

0000-0001-7072-2656
Instituto de Biologia, Universidade Federal da Bahia, 40.026-010, Salvador, BA (Brazil)

(5)

0000-0003-4342-2089
Tropical Diversity Section, Royal Botanic Garden Edinburgh, EH3 5NZ, Edinburgh (United Kingdom)

(6)

0000-0001-8230-2501
Wageningen University, Plant Ecology and Nature Conservation Group, 6700 AK, Wageningen (Netherlands)

(7)

0000-0001-7436-0939
Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, 440369-00, Feira de Santana, BA (Brazil)

(8)

0000-0003-4508-0131
Colegiado de Ecologia, Universidade Federal do Vale do São Francisco, 563049-17, Senhor do Bonfim, BA (Brazil)

(9)

0000-0002-4075-462X
Universidade Federal de Lavras, 37200-900, Lavras, MG (Brazil)

(10)

Tropical Diversity Section, Royal Botanic Garden Edinburgh, EH3 5NZ, Edinburgh (United Kingdom)

(11)

0000-0002-8196-288X
University of Exeter, EX4 4QG, Exter (United Kingdom)

(12)

0000-0002-8993-6168
School of Geography, University of Leeds, LS2 9JT, Leeds (United Kingdom)

Corresponding author

Robson Borges De Lima
robson.lima@ueap.edu.br

Citation

Viana Santos HK, Borges De Lima R, Figueiredo De Souza RL, Cardoso D, Moonlight PW, Teixeira Silva T, Pereira De Oliveira C, Alves Júnior FT, Veenendaal E, Paganucci De Queiroz L, Rodrigues PMS, Dos Santos RM, Sarkinen T, De Paula A, Barreto-Garcia PAB, Pennington T, Phillips OL (2023). Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil. iForest 16: 116-126. - doi: 10.3832/ifor4104-016

Academic Editor

Emanuele Lingua

Paper history

Received: Mar 24, 2022
Accepted: Feb 14, 2023

First online: Apr 17, 2023
Publication Date: Apr 30, 2023
Publication Time: 2.07 months

Open Access

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