Water balance partitioning for ecosystem service assessment. A case study in the Amazon

Casagrande, Enrico; Recanati, Francesca; Rulli, Maria Cristina; Bevacqua, Danièle; Melià, Paco

doi:10.1016/j.ecolind.2020.107155

Cited by 28 publications

(19 citation statements)

References 79 publications

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“…The Amazon rainforest is the largest tropical forest in the world, with several ecological benefits for the planet, such as, for example, fundamental environmental services related to water; sequestration of atmospheric CO2 and diversity of animals, plants and microorganisms (Bendel & Stephens 2020, Casagrande et al, 2021, Souza et al, 2021. Currently, this forest is constantly threatened by changes in land use, in particular by deforestation (Casagrande et al, 2021). From this point of view, it is essential to study management systems that promote sustainable land use in these regions, enabling economic…”

Section: Discussionmentioning

confidence: 99%

Quantification of biomass and litter in agroforestry system with sour orange cultivation in the Brazilian Amazon

Filho

Kato

Galvão

et al. 2021

RSD

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The knowledge of the quantity and composition of the deposited biomass is useful to plan the nutrient management of cultivations in agroforestry systems. The objective of this work was to evaluate the production of biomass and litter in two agroforestry systems with organic and conventional cultivations of sour orange. The areas use models of orange production by monoculture and under agroforestry systems: the first agroforestry system is composed of rows of brazilian mahogany (Swietenia macrophylla K.) accompanied by double rows of orange trees (Citrus aurantium L.); the second system is composed of rows of ingá (Ingá edulis Mart.) accompanied by double rows of orange trees. A completely randomized design was used in a 10x2 factorial scheme, with 4 replications. The locations within the management systems were organized as follows: agroforestry system composed of mahogany trees; Ingá trees agroforestry system; conventional sour orange monoculture system. The areas that the biomass and litter were collected in the locations in the systems were: between plants in the row for cultivation of forest species that make up the system; between rows of the forest species row and orange cultivation row; between plants in the orange cultivation row; between rows of the double row of orange cultivation. Two periods were analyzed in the experiment: the months of lowest and highest rainfall. Agroforestry systems promoted greater biomass and litter to the soil compared to monoculture. In this way, they were configured as a beneficial practice for the soil in sour orange crops in the Brazilian Amazon.

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Section: Discussionmentioning

confidence: 99%

Quantification of biomass and litter in agroforestry system with sour orange cultivation in the Brazilian Amazon

Filho

Kato

Galvão

et al. 2021

RSD

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“…The AM biome has tropical rainforest climate with high air temperatures (Casagrande et al 2021;Nobre et al 2016); CT and CE face frequent droughts, and their natural species with increasing aridity develop resilience (Almagro et al 2017;Azevedo et al 2020;Jardim et al 2022;Sano et al 2019); PT is the largest tropical wetland in the world, with two well-defined seasons: a rainy summer and a dry winter (Assine et al 2015, Marengo et al 2021; AF presents a humid tropical climate (Ribeiro et al 2009), however, with contrasting microclimates among natural and anthropized areas (Souza et al 2020); and PP has temperate climate and low air temperatures (Roesch et al 2009;Rubert et al 2018).…”

Section: Biomes and Data Setmentioning

confidence: 99%

“…In the Brazilian biomes, there is a large diversify of natural species and agricultural crops (Lewinsohn and Prado 2005) which are suffering of several environmental impacts, as deforestations; burnings; air, water and soil pollutions, as well intensive agricultural crops replacing natural species (Casagrande et al 2021;Mariano et al 2018). These environmental problems demand large-scale studies to support sustainable explorations of the natural resources (Araujo et al 2019;Jardim et al 2022;Leivas et al 2015a, b;Nuñez et al 2017;Santos et al 2020;Teixeira et al 2021a, b).…”

Section: Introductionmentioning

confidence: 99%

Monitoring environmental indicators by coupling remote sensing and weather data: applications to the Brazilian biomes

Teixeira

Leivas

Takemura

et al. 2022

Preprint

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The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale environmental indicators in the Brazilian biomes. The MODIS MOD13Q1 reflectance product and weather data were used along the year 2016. The analyzed biomes were Amazon (AM), Caatinga (CT), Cerrado (CE), Pantanal (PT), Atlantic Forest (AF), and Pampa (PP). Significant differences on precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P - ET) and water productivity (WP = ET/BIO). The highest WB and WP along the year were for the wettest AM, AF, and PP biomes, when compared with the driest CT. Precipitation (P) distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e, the ratio of ET to reference evapotranspiration (ET0), however there was a gap between ETf and WB, what can be related to the time needed for recovering the good conditions of soil moisture levels after rainfalls. For some biomes, BIO was related to the levels of absorbed photosynthetically active radiation (PARabs), which depends on the leaf area and soil cover (AM, AF, and PP), while for others BIO followed the soil moisture levels, represented by ETf (CT, CE, and PT). The large-scale modelling presented suitability for monitoring environmental parameters at a 250-m spatial and 16-day spatial and temporal resolutions, with great potential to subsidize public policies regarding the management and conservation of the natural resources, with possibility for replication of the methods in other countries.

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“…Crossing the Figures 1a and 1b, Table 1 shows the matrix corresponding to the areas and percentual of the biomes inside each geographic region. The Amazon biome has tropical rainforest climate with high air temperatures (Casagrande et al 2021;Nobre et al 2016); Caatinga and Cerrado face frequent droughts, and their natural species develop resilience with increasing aridity under these dry conditions (Almagro et al 2017;Azevedo et al 2020;Jardim et al 2022;Sano et al 2019;Santos et al 2014); Pantanal is the largest tropical wetland in the world, with two well-defined seasons:…”

Section: Introductionmentioning

confidence: 99%

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

Teixeira

Leivas

Takemura

et al. 2023

Preprint

View full text Add to dashboard Cite

The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in the Brazilian biomes. The MODIS MOD13Q1 reflectance product and gridded weather data were used for the year 2016. The analyzed biomes were Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant differences on precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P - ET) and water productivity (WP = ET/BIO). The highest WB and WP differences along the year were for the wettest Amazon, Atlantic Forest, and Pampa biomes, when compared with the driest Caatinga biome. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e, the ratio of ET to reference evapotranspiration (ET0), however there was a gap between ETf and WB, what can be related to the time needed for recovering the good soil moisture conditions after the rainy seasons. For some biomes, BIO was more related to the levels of absorbed photosynthetically active radiation (Amazon, Atlantic Forest, and Pampa), while for others BIO followed more the soil moisture levels, represented by ETf (Caatinga, Cerrado, and Pantanal). The large-scale modelling presented suitability for monitoring environmental indicators, opening the room to detect anomalies for specific periods along the year by using historical images and weather data, with great potential to subsidize public policies regarding the management and conservation of the natural resources and possibility for replication of the methods in other countries.

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Water balance partitioning for ecosystem service assessment. A case study in the Amazon

Cited by 28 publications

References 79 publications

Quantification of biomass and litter in agroforestry system with sour orange cultivation in the Brazilian Amazon

Quantification of biomass and litter in agroforestry system with sour orange cultivation in the Brazilian Amazon

Monitoring environmental indicators by coupling remote sensing and weather data: applications to the Brazilian biomes

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

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