Eduardo Souza

Prof. Eduardo Souza

Federal Rural University of Pernambuco
orcid

Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2017 in Journal of Arid Environments
Verified
Journal Article
Closed access
PSPaulo Ferreira da Silva
Paulo Ferreira da Silva
JLJosé Romualdo Lima
José Romualdo Lima
AAAntonio Celso Dantas Antonino
Antonio Celso Dantas Antonino
RSRodolfo Souza
Rodolfo Souza
ESEduardo Souza
Eduardo Souza
EAEdevaldo Miguel Alves
Edevaldo Miguel Alves

24 June 2016 in Hydrological Processes
Verified
Journal Article
Closed access
PDF file
RSRodolfo Souza
Rodolfo Souza
XFXue Feng
Xue Feng
AAAntonio Antonino
Antonio Antonino
SMSuzana Montenegro
Suzana Montenegro
ESEduardo Souza
Eduardo Souza
Amilcare PorporatoAmilcare Porporato
Amilcare Porporato

10 November 2021 in Water Resources Research
Verified
Journal Article
Open access
PDF file
DMDavi Melo
Davi Melo
JAJamil Alexandre Ayach Anache
Jamil Alexandre Ayach Anache
VBValéria Peixoto Borges
Valéria Peixoto Borges
Diego MirallesDiego Miralles
Diego Miralles
BMBrecht Martens
Brecht Martens
EWEdson Wendland
Edson Wendland
Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land‐use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

11 September 2017 in Ecohydrology
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Journal Article
Closed access
PDF file
PLPedro Leite
Pedro Leite
ESEduardo Souza
Eduardo Souza
RGRafael J. Gomes
Rafael J. Gomes
JCJosé R. Cantalice
José R. Cantalice
Bradford WilcoxBradford Wilcox
Bradford Wilcox

1 January 2021 in Soil and Tillage Research
Verified
Journal Article
Closed access
RSRodolfo Souza
Rodolfo Souza
SHSamantha Hartzell
Samantha Hartzell
AFAndré Ferraz
André Ferraz
AAAndré Quintão de Almeida
André Quintão de Almeida
JLJosé Romualdo de Sousa Lima
José Romualdo de Sousa Lima
ESEduardo Souza
Eduardo Souza

4 August 2021 in Ecology and Evolution
Verified
Journal Article
Open access
PDF file
CWCynthia L. Wright
Cynthia L. Wright
ALAndré L. A. de Lima
André L. A. de Lima
ESEduardo Souza
Eduardo Souza
JWJason B. West
Jason B. West
Bradford WilcoxBradford Wilcox
Bradford Wilcox
In seasonally dry tropical forests, plant functional type can be classified as deciduous low wood density, deciduous high wood density, or evergreen high wood density species. While deciduousness is often associated with drought‐avoidance and low wood density is often associated with tissue water storage, the degree to which these functional types may correspond to diverging and unique water use strategies has not been extensively tested. We examined (a) tolerance to water stress, measured by predawn and mid‐day leaf water potential; (b) water use efficiency, measured via foliar δ13C; and (c) access to soil water, measured via stem water δ18O. We found that deciduous low wood density species maintain high leaf water potential and low water use efficiency. Deciduous high wood density species have lower leaf water potential and variable water use efficiency. Both groups rely on shallow soil water. Evergreen high wood density species have low leaf water potential, higher water use efficiency, and access alternative water sources. These findings indicate that deciduous low wood density species are drought avoiders, with a specialized strategy for storing root and stem water. Deciduous high wood density species are moderately drought tolerant, and evergreen high wood density species are the most drought tolerant group. Synthesis. Our results broadly support the plant functional type framework as a way to understand water use strategies, but also highlight species‐level differences.