Ralph TrancosoUniversity of Queensland / Queensland Government · School of Biological Sciences / Department of Environment and Science
Ralph Trancoso
Doctor of Philosophy
Climate change, Climate impacts, Hydrological impacts, Deforestation impacts
About
47
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Introduction
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February 2013 - December 2016
Publications
Publications (47)
Market and public policies govern deforestation trends and patterns globally. Here I show that in the Brazilian Amazon, the largest tropical forest in the world, the size of deforestation polygons – the individual portions of cleared forest patches – has significantly increased in response to the current environmental governance. The average size o...
Deforestation exacerbates climate change through greenhouse gas emissions, but other climatic alterations linked to the local biophysical changes remain poorly understood. Here, we assess the impact of tropical deforestation on fire weather risk – that is the climate conditions conducive to wildfires – using high-resolution convection-permitting cl...
Heatwaves are defined as unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. This paper investigates: 1) changes in heatwave characteristics such as peak temperature, number of events, frequency and duration over a past 67-year period in Australia;...
Changes in the hydrological cycle have a significant impact in water-limited environments. Globally, some of these regions are experiencing declining precipitation trends yet are simultaneously becoming greener, partly due to vegetation feedbacks associated with increasing atmospheric CO2 concentrations. Reduced precipitation together with increasi...
The spatial and temporal heterogeneity of climate, soils, topography and vegetation control the water and energy balances among catchments. Two well-known hydrological theories underpinning these processes are the Budyko framework and the Dunne diagram. Relating the scaling of water–energy balances (Budyko) and runoff generation mechanisms (Dunne)...
High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 GCMs to a 10 km resolution over Australia using the Conforma...
Climate change is predicted to significantly alter hydrological cycles across the world, affecting runoff, streamflow, and pollutant loads from diffuse sources. The objectives of this study were to examine the impacts of climate change on streamflow, total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) loads in the subtrop...
Boreal forests play a crucial role in the global carbon (C) cycle and in climate stabilization. To better predict global C budgets, it is important to accurately estimate the size of forest C pools, and to identify the factors affecting them. We used national forest inventory data for the Greater Khingan Mountains, northeast China from 1999 to 2018...
A multi-scenario, multi-model ensemble of simulations from regional climate models is outlined to provide the core data source for a set of climate projections and a climate change service. A subset of realisations from CMIP6 Global Climate Models (GCMs) are selected for downscaling by Regional Climate Models (RCMs) under a ‘sparse matrix’ framewor...
Climate change is expected to significantly alter river hydrological regimes throughout the world, affecting water resources and the frequency of floods and droughts. The objectives of this study were to determine the impacts of climate change and sea level rise on streamflow and floodplain inundation in the subtropical Logan-Albert catchment, Aust...
Both deforestation and El Niño events influence Borneo’s climate, but their interaction is not well understood. Borneo’s native forest cover decreased by 37.1% between 1980 and 2015 with large areas being replaced by oil palm and a mosaic of plantations and regrowth vegetation. The island is also affected by El Niño events, resulting in severe drou...
Tree age (AGE) and stocking degree (P) strongly influence tree shape, but their effects have been neglected in most tree profile equations. In addition, data used to build traditional tree profile equations usually do not meet the statistical requirements of independence and identical distribution of observations. Therefore, our main objectives wer...
Estimating timber volume and carbon stock in forests is fundamental for silviculture and for accurate estimation of national and global carbon budgets. Taper models are important tools for predicting diameter at any height along a tree bole. Mean annual temperature (MAT) and mean annual precipitation (MAP) influence tree growth, but their precise e...
Climate and soil factors drive forest carbon (C) density. However, their impacts on the aboveground carbon density (ACD) and belowground carbon density (BCD) of global forest types have not been quantified in previous studies. In this study, we compiled global forest biomass data that included 8800 plots to better quantify the changes in total carb...
The summer of 2018-19 was the hottest on record for Australia. The extreme heatwaves and bushfires that occurred across Queensland are a clear indication that we are facing unprecedented challenges in understanding and responding to the impacts of natural hazards in a changing climate.
The State Heatwave Risk Assessment (SHRA) was developed to pro...
Heatwaves are unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. Heatwaves have increased globally over the last century and are projected to achieve unprecedented levels by the end of the current century in absence of strong mitigation measures....
Analyses of trends in observed floods often focus on relatively frequent events, whereas changes in rare floods are only studied for a small number of locations that have exceptionally long observational records. Understanding changes in rare floods is especially relevant as these events are often most damaging and influence the design of major str...
Analyses of trends in observed floods often focus on relatively frequent events, whereas changes in rare floods are
only studied for a small number of locations that have exceptionally long observational records. Understanding
changes in rare floods is especially relevant as these events are often most damaging and influence the design of
major str...
The terrestrial water cycle is altered by climate and land surface changes, but the impact these changes have on river floods is uncertain. Analyses of trends in observed floods often focus on relatively frequent events (e.g. annual peaks or peaks over threshold), whereas changes in rare floods are only studied for a small number of locations that...
Streamflow characteristics are driven by specific flow-generation mechanisms, which are in turn determined by the biophysical properties of catchments. They provide important environmental services for society and ecosystems, regulating water supply and quality, flood mitigation, and the biological diversity of aquatic ecosystems. This study invest...
The Cerrado is a biome in Brazil that is experiencing the most rapid loss in natural vegetation. The objective of this study was to analyze the changes in the spectral response in the red, near infrared (NIR), middle infrared (MIR), and normalized difference vegetation index (NDVI) when native vegetation in the Cerrado is deforested. The test sites...
relatos de pesquisa 130 1. Introdução estimativas recentes sobre a per-da de cobertura vegetal nativa apontam a América do Sul e a áfrica como os continentes que vêm perdendo mais rapidamente suas florestas 4 . O Brasil, seguido da indonésia, foram os países com maior área desmatada entre 1990 e 2005. Além de liderar o ranking mundial de desmatamen...
REMOTE SENSING OF VEGETATION FOR MONITORING DEFORESTATION IN CERRADO AND LAND CATEGORIES IN THE AMAZON
This Master Science thesis used remote sensing of vegetation to carry out two studies in two Brazilian biomes, which present different vegetation characteristics.
The first study was performed in Cerrado biome, covering the Brazilian savannas tha...
The Mato Grosso and Pará are the Amazonian states that have been contributing to the major part of deforestation in Brazilian Amazon. Between 1988 and 2011 their deforestation represented 68% of overall deforestation in Brazilian Amazon. The aim of this paper is to make a comparative evaluation of Normalized Difference Vegetation Index (NDVI), Enha...
Graphical abstract
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Highlights
► DHSVM model evaluation for three nested basins in Central Amazonia. ► Tropical rainforest catchment with deep soil successfully modeled by DHSVM. ► High-resolution soil and vegetation maps obtained from SRTM-derived HAND model. ► HAND model useful in deriving spatial distributions of...
This chapter argues for a broader conceptual domain provided by agroforestry practices as a key pathway for the reorientation of agricultural systems in the Amazon toward modes of production that combine productivity and sustainability. A contextualization of the multiple expressions of current agroforestry development in the Amazon shows that, con...
Homegardens are a common feature of indigenous dwellings in the savannas of Roraima, northern Brazil. In order to evaluate
the effect of homegardens on soils, samples were taken in 5 sites each in the categories new homegardens (0–10-years old), established homegardens (15–35-years old) and old homegardens (more than 40-years old) and in adjacent s...
Conserving natural vegetation cover is of critical importance for maintaining the ecological integrity and hydrological properties of large river basins (more than 100 000 km2). Recent estimates indicate that more than 700 000 km2 of Brazilian Amazon have already been deforested, and to reduce further losses and preserve the important natural and c...
One of the largest uncertainty factors of future scenarios of global climate is related to the feedback mechanisms among the land cover and hydrological components in the Amazon basin. It is still necessary to improve the knowledge of how the rainfall patterns are affected or redistributed by deforestation and/or regrowth of the vegetation. Studies...
More than 700000 Km2 have already deforested in Brazilian Legal Amazon. Although every year large forested areas have been converted to pasture and agriculture lands, the land cover changes patterns are highly heterogenic in Brazilian Amazonia. Several factors driving the land cover changes patterns, among then: the most important are: access, infr...
A área drenada pelos rios que formam a parte sul da bacia amazônica abrange seis dos nove estados integrantes da Amazônia legal. A derrubada da floresta, que se intensificou a partir dos anos 70, atinge principalmente essa faixa, banhada por sete grandes rios (Tocantins, Araguaia, Xingu, Tapajós, Madeira, Purus e Juruá). As maiores áreas desflorest...
Changes in land cover and alterations in the hydrological response of catchments in Amazonia.
To evaluate the hydrological impacts of deforestation, three studies at different spatial scales, from regional to local were realized. At the first, scale, the larger basins of Amazonia have been delineated to quantify the area of deforestation and prote...
Fires in the Amazon forest are mainly concentrated in a region known as the "Arc of deforestation¨. Commonly, fires escape beyond their intended boundaries and spread into nearby forest. The objective of this study was to (1) understand the spatial relation between hotspot counts and land-use/land-cover change in the Brazilian Legal Amazônia and (2...
The Amazon basin is rather known by their peculiar ecossystem with high biodiversity spreaded out by a large drainage basin which produces almost 15% of the world's drinking water. The human impacts of deforestation during he last 30 years are responsible for about 653.000Km2 of a clear forest surface shaped and denominated as the deforestation arc...
The objective of this experiment was to relate the silvicultural and environemtal differences proportionate by biological measures, on the ground reconstruction; the infiltration was a discriminante element on the evaluation of the effects of estruturation, aggregation and transformation of the litolic material in the first millimeters of the sub-s...
This work intended to know the dynamics of recovery of gullies after implantation of physical measures, using the recruitins species sproutins as indicator. Two adjacents hidrological stretch, both located between 75 and 112 m high (over sea level), each one presentins one gully, that was recovered by physical measures. Sazonal florístic survey was...
Questions
Questions (2)
The effect of climate and land use/cover changes on streamflow of non-experimental catchments has long drawn the attention of water resource scientists. Numerous approaches have been proposed to tackle this issue, among the most popular are:
- Trend analysis of hydro-climatological and vegetation time series (i.e., Kahya and Kalayci, JoH, 2004);
- Comparison between pre and post change periods using time series (i.e., Costa et al., JoH, 2003);
- Hydrological modelling calibrated against data before change and applied after change followed by a comparison with post change time series (i.e., Wilk et al., HP, 2001; Rodriguez et al., HP, 2010);
- Water and energy excess in the context of the Budyko framework (i.e., Tomer and Schilling, JoH, 2009; Roderick and Farquhar, WRR, 2011).
What are the other relevant approaches and which of them are more reliable with regard to accuracy, popularity and evidences in scientific literature?
Recognizing there is not a definitive answer for this question, the aim here is to stimulate a debate and put together different opinions, experiences and constructive discussion about this topic.
The selection of input variables is critical in order to find the optimal function in ANNs. Studies have been pointing numerous algorithms for input variable selection (IVS). They are generally classified in three different groups: (1) dimension reduction, (2) variable selection, and (3) filter. Each group holds several algorithms with specific assumptions and limitations.
If a researcher decides to use ANN, he might be happy to know...
1) Which approach is the most recommended to select ANN input variables?
2) What are the advantages and drawbacks of your choice in regard to other strategies?
3) Is the algorithm implemented in any statistical package (R or other free ones are more approachable)?
