Ana Maria Heuminski de Avila, Bruno Kabke Bainy
Ano de publicação: 2022
Ano de publicação: 2019
o presente artigo apresenta a reconstrução histórica dos eventos e documentos que caracterizaram a institucionalização do ambiente em Moçambique, entre 1980 e 2014. Inicialmente, apresenta a metodologia que orientou o artigo e debates teóricos, estabelecendo diálogo entre a História Ambiental da América Latina, abordagens pós-coloniais e Sociologia do Conhecimento. Na sequência, apresenta os eventos que delimitaram a dimensão local dos riscos ambientais, e documentos que marcaram a visão global destes.
Jurandir Zullo Junior, Luciana Alvim Santos Romani
Ano de publicação: 2019
classification models is a costly task, both in terms of difficult to
find suitable samples as well as their quantity. In this sense, Active
Learning (AL) improves the training set building by providing an
efficient way to select only essential data to be attached to the
training set, consequently reducing its size and even enhancing model's
accuracy, when compared to random sample selection. In this paper, we
proposed a framework for time series classification in order to monitor
sugarcane area in São Paulo, Brazil. The AL approach consisted of
selecting seasonal time series information from less than 1 percent of
each class' pixels to build the training set and evaluate this selection
by an expert user supported by distance measurements, repeating this
process until both distance measurement thresholds were satisfied. In
most years, the classification results presented about 90 percent of
correlation with official estimates based on both traditional and
satellite image analysis methods. This framework can then help Land Use
Change (LUC) monitoring as it produced similar results compared to other
methods that demands more human and financial resources to be adopted.
Ano de publicação: 2019
will continue to act as a carbon sink in the future, primarily owing to
the rising atmospheric carbon dioxide (CO2) concentration.
Soil phosphorus impoverishment in parts of the Amazon basin largely
controls its functioning, but the role of phosphorus availability has
not been considered in global model ensembles—for example, during the
Fifth Climate Model Intercomparison Project. Here we simulate the
planned free-air CO2 enrichment experiment AmazonFACE with an
ensemble of 14 terrestrial ecosystem models. We show that phosphorus
availability reduces the projected CO2-induced biomass carbon growth by about 50% to 79 ± 63 g C m−2 yr−1
over 15 years compared to estimates from carbon and carbon–nitrogen
models. Our results suggest that the resilience of the region to climate
change may be much less than previously assumed. Variation in the
biomass carbon response among the phosphorus-enabled models is
considerable, ranging from 5 to 140 g C m−2 yr−1,
owing to the contrasting plant phosphorus use and acquisition strategies
considered among the models. The Amazon forest response thus depends on
the interactions and relative contributions of the phosphorus
acquisition and use strategies across individuals, and to what extent
these processes can be upregulated under elevated CO2.
Carbon cycle, Climate and Earth system modelling, Climate-change ecology, Element cycles, Tropical ecology.
Ano de publicação: 2019
climate change has been incorporated into governmental agendas, and
evaluate the status of adaptation planning and interventions at the
local level. In this paper, we seek to contribute towards bridging this
gap by identifying local practices connected to climate adaptation in
six large Brazilian cities, and presenting a framework, based on the
existing literature, for assessing constraints to adaptation across the
municipal level. Although local governments are not the only actors who
can take the lead through their actions, the employed framework
considers that effective adaptation planning in urban areas is highly
dependent on municipal efforts. Our findings indicate that six aspects
have the highest levels of impact on adaptation in the Brazilian cities
studied: administrative practices, political will, level of commitment,
mismatch between the scale of urban issues and the extent of local
government authority, pressures from private sectors, and inspection.
Although these barriers are not specific only to climate issues and can
be identified in other environmental arenas, when combined, they cause
and worsen constraints to advancing urban adaptation at the local level.
Specifically concerning the local dynamics of urban planning, the
combination of pressures from private sectors and insufficient
inspection negatively affects the ability of these cities to consolidate
adaptation interventions. Our results are helpful in the context of
large cities, particularly in Global South, where, as in Brazil,
competitive urbanism and specific interest groups confront municipal
efforts, and make achieving adaptation more difficult.
Priscila Pereira Coltri, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2019
identify the spatio-temporal trend of São Paulo’s coffee cultivation
area. Our hypothesis is that coffee cultivation area has been changing
significantly in the study area since 1990. Therefore, the main goal of
this research was to map the spatial pattern of coffee land use change.
For coffee land use diagnostics, official data of cultivated area,
hotspot analyses and growth rate were used. The results demonstrated
that coffee cultivation area decreased and concentrated in smaller
areas, which are traditionally recognized as “coffee quality regions”.
The producer size analyses evidenced that, not only the localization,
but also the producer profile changes as well. Smallholders increased
but medium and large producers decreased significantly in the studied
period. The coffee abandonment analyses demonstrated that, over the
study period, 51.46% of the coffee area cultivated in the study region
was abandoned.
Ano de publicação: 2019
Payment for ecosystem services,
Public policies,
Sugarcane production,
Participatory methods,
Cairngorms National Park
Ano de publicação: 2019
is crucial for the planning and management of water resources and
agricultural production. In this study, the applicability of the
Hargreaves Samani (HS), artificial neural network (ANN), multiple linear
regression (MLR) and extreme learning machine (ELM) models were
evaluated to estimate ET0 based on temperature data from the
Verde Grande River basin, southeastern Brazil. These models were
evaluated in two scenarios: local and pooled. In the local scenario,
training, calibration and validation of the models were performed
separately at each station. In the pooled scenario, meteorological data
from all stations were grouped for training and calibration and then
separately tested at each station. The ET0 values estimated
by the Penman-Monteith model (FAO-56 PM) were considered the target
data. All the developed models were evaluated by cluster analysis and
the following performance indices: relative root mean square error
(RRMSE), Pearson correlation coefficient (r) and Nash-Sutcliffe
coefficient (NS). In both scenarios evaluated, local and pooled, the
results revealed the superiority of the artificial intelligence methods
(ANN and ELM) and the MLR model compared to the original and adjusted HS
models. In the local scenario, the ANN (with r of 0.751, NS of 0.687
and RRMSE of 0.112), ELM (with r of 0.747, NS of 0.672 and RRMSE of
0.116) and MLR (with r of 0.743, NS of 0.665 and RRMSE of 0.068) models
presented the best performance, in addition to being grouped in the same
cluster. Similar to the observations from the local scenario, the ANN
(with r of 0.718, NS of 0.555 and RRMSE of 0.165), ELM (with r of 0.724,
NS of 0.601 and RRMSE of 0.151) and MLR (with r of 0.731, NS of 0.550
and RRMSE of 0.091) models presented the best performance in the pooled
scenario and were grouped in the same cluster. The locally trained
models presented higher precision than the models generated with pooled
data; however, the models generated in the pooled scenario could be used
to estimate ET0 in cases of unavailability of local
meteorological data. Although the MLR, ANN and ELM models, based on
temperature data, are appropriate alternatives to accurately estimate ET0
in the Verde Grande River basin, southeastern Brazil, the MLR model
presents the advantage of the use of explicit algebraic equations,
facilitating its application.
Soft computing, Artificial neural networks, Multiple linear regression, Extreme learning machines, Artificial intelligence, Meteorological data
Jurandir Zullo Junior, Priscila Pereira Coltri, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2019
Ano de publicação: 2019
Hilton Silveira Pinto, Jurandir Zullo Junior, Priscila Pereira Coltri, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2019
Agriculture,
Environmental science.
Ano de publicação: 2019
Ano de publicação: 2018
Integrated valuation,
Ecosystem service appraisal,
Ecosystem service governance,
Information costs,
Uncertainty,
Valuation,
Eccosystem services cascade
Ano de publicação: 2018
Dispersão de poluentes, Foguetes, [en] GILTT, [en] Pollution dispersion, [en] Volume source,
Ano de publicação: 2018
The scientific notion that the Amazon forest could be deeply impacted by climate change through large-scale replacement of the rainforest by a drier forest, a savannah or even nonanalogous degraded vegetation will soon be 20 years old (White et al., 1999; Cox et al., 2000). The mere prospect of undermining a significant fraction of the world's largest tropical rainforest due to global climate change – even if deforestation is completely stopped – should be alarming for the nine Amazonian countries, and the world as a whole, given the bundled ecosystem services at stake. This possibility, however, has not caused widespread concern among governments and societies because the lingering scientific uncertainties prevent any well-informed decisions from being made. The most pressing of these uncertainties regarding the resilience of the Amazon forest to ongoing climatic changes and rising atmospheric CO2 concentrations are as follows:
- the impacts of the future rainfall regime – either drier, wetter or simply more seasonal – on the forest's structure and functioning
- the existence and extent of nutrient – notably phosphorus (P) – limitation on forest productivity
- the existence, magnitude and duration of a supposed CO2 fertilization effect.
Ano de publicação: 2018
zoneamento agrícola, sensoriamento remoto, geoprocessamento.
Ano de publicação: 2018
Ano de publicação: 2018
BIOLOGICAL SCIENCES, ENVIRONMENTAL SCIENCES, SOCIAL SCIENCES, SUSTAINABILITY SCIENCE
Ano de publicação: 2018
Ano de publicação: 2018
Ano de publicação: 2017
Ana Maria Heuminski de Avila, Gabriel Constantino Blain, Hilton Silveira Pinto, Regina Célia de Matos Pires, Vânia Rosa Pereira
Ano de publicação: 2017
Ana Maria Heuminski de Avila, Gabriel Constantino Blain, Vânia Rosa Pereira
Ano de publicação: 2017
Ano de publicação: 2016
Ano de publicação: 2016
Ano de publicação: 2016
Ano de publicação: 2016
Ano de publicação: 2015
Priscila Pereira Coltri, Hilton Silveira Pinto, Jurandir Zullo Junior
Ano de publicação: 2015
Eduardo Delgado Assad, Hilton Silveira Pinto
Ano de publicação: 2014
Martha Delphino Bambini, Andre Tosi Furtado, Jurandir Zullo Junior, Priscila Pereira Coltri
Ano de publicação: 2014
Luciana Alvim Santos Romani, Priscila Pereira Coltri
Ano de publicação: 2014
Luciana Alvim Santos Romani, Ana Maria Heuminski de Avila, Jurandir Zullo Junior
Ano de publicação: 2013
Eduardo Delgado Assad, Hilton Silveira Pinto
Ano de publicação: 2013
Priscila Pereira Coltri, Hilton Silveira Pinto, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2013
Eduardo Delgado Assad, Hilton Silveira Pinto
Ano de publicação: 2013
Eduardo Delgado Assad, Hilton Silveira Pinto
Ano de publicação: 2013
Renata Ribeiro do Valle Gonçalves, Agma Juci Machado Traina, Cristina R. Nascimento, Jurandir Zullo Junior, Luciana Alvim Santos Romani
Ano de publicação: 2012
Renata Ribeiro do Valle Gonçalves, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Priscila Pereira Coltri
Ano de publicação: 2011
Priscila Pereira Coltri, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2011
Renata Ribeiro do Valle Gonçalves, Agma Juci Machado Traina, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani
Ano de publicação: 2011
Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2011
Jurandir Zullo Junior, Ana Maria Heuminski de Avila, Eduardo Delgado Assad, Hilton Silveira Pinto
Ano de publicação: 2011
Greice Martins de Freitas, Alexandre Xavier Falcão, Ana Maria Heuminski de Avila, Hilton Silveira Pinto, João Paulo Papa
Ano de publicação: 2010
Andrea de Oliveira Cardoso, Ana Maria Heuminski de Avila, Hilton Silveira Pinto, Pedro Leite da Silva Dias
Ano de publicação: 2010
Cristina Rodrigues Nascimento, Jurandir Zullo Junior
Ano de publicação: 2010
João Paulo Papa, Alexandre Xavier Falcão, Ana Maria Heuminski de Avila, Greice Martins de Freitas
Ano de publicação: 2009
Raquel Ghini, Emília Hamada, José Clério R. Pereira, Luadir Gasparotto, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2008
Renata Ribeiro do Valle Gonçalves, Jurandir Zullo Junior
Ano de publicação: 2008
Raquel Ghini, Emília Hamada, Mário José Pedro Júnior, Renata Ribeiro do Valle Gonçalves
Ano de publicação: 2008
Voltar