Impacts of tropical forest cover on water quality in agricultural watersheds in southeastern Brazil

Mello, Kaline de; Valente, Roberta Averna; Randhir, Timothy O.; Vettorazzi, Carlos Alberto

doi:10.1016/j.ecolind.2018.06.030

Cited by 84 publications

(49 citation statements)

References 37 publications

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“…Interestingly, SRP retention was related to discharge in our agricultural streams (Table ). As agriculture is expected to indirectly change the hydrological regime through modifications of different components of the hydrological cycle (e.g., surface runoff and interception; Mello, Valente, Randhir, & Vettorazzi, ), we expect implications for SRP removal as such components directly influence discharge.…”

Section: Discussionmentioning

confidence: 99%

Agriculture influences ammonium and soluble reactive phosphorus retention in South American headwater streams

et al. 2019

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Agricultural activities can affect the delivery of nutrients to streams, riparian canopy cover, and the capacity of aquatic systems to process nutrients and sediments. There are few measures of nutrient uptake and metabolism from tropical or subtropical streams in general, and even fewer from tropical regions of South America. We examined ammonium (NH4+) and soluble reactive phosphorus (SRP) retention in streams in Brazil and Argentina. We selected 12 streams with relatively little or extensive agricultural activity and conducted whole‐stream nutrient additions and measurements of gross primary production and ecosystem respiration. We used multiple linear regression to determine potential drivers of nutrient uptake metrics across the streams. Nutrient concentrations and retention differed significantly between land use categories. Both NH4+ and SRP concentrations were higher in the agricultural sites (means of 161 and 495 μg l–1, respectively), whereas metabolic rates were slower and transient storage was smaller. Our analysis indicated that agriculture increased ambient uptake lengths and decreased uptake velocities. The regression models revealed that ambient SRP had a positive effect on NH4+ uptake and vice versa, suggesting strong stoichiometric controls. Drivers for nutrient uptake in streams with low‐intensity agriculture also included canopy cover, temperature, and ecosystem respiration rates. Nutrient assimilation in agricultural sites was influenced by a higher number of variables (gross primary production for SRP, discharge, and transient storage for both nutrients). Our results indicate agricultural activity changes both the magnitude of in‐stream nutrient uptake and the mechanisms that control its variation, with important implications for South American streams under agricultural intensification.

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Section: Discussionmentioning

confidence: 99%

Agriculture influences ammonium and soluble reactive phosphorus retention in South American headwater streams

et al. 2019

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“…Recent human activity has increased industrial agriculture (i.e. soy, cotton and corn) and extensive cattle ranches leading to deforestation and associated decrease in stream water quality (Barona et al 2010;Durigan et al 2013;de Mello et al 2018b;Stella and Bendix 2019). A more reliable road system has also opened not only the agrarian frontier (Schmink et al 2019) (Junk et al 1989).…”

Section: Methodsmentioning

confidence: 99%

“…Although Amazonian deforestation rates appeared to be slowing in the first decade of the 21 st century (Nepstad et al 2014), since then, they have continually increased to unprecedented levels (Escobar 2019a, Ferrante andFearnside 2019) as Brazil's recent policies have progressively weakened environmental laws in favor of the energy production and agribusiness sectors (Rajão and Georgiadou 2014;Brancalion et al 2016;Fearnside 2016a;Abessa et al 2019;Ferrante and Fearnside 2019;Scarrow 2019). Across the Amazon, the construction of roads that enable transport of timber (legal and illegal), deforestation for cattle ranching and the establishment of large monocultures (e.g., soy, corn, cotton) are the leading causes of Amazonian deforestation and deterioration of soil and water quality (Abell et al 2011;Durigan et al 2013;Macedo et al 2013;Dias et al 2015;Lessa et al 2015;Lees et al 2016;Marmontel et al 2018;de Mello et al 2018a;de Mello et al 2018b;Rodrigues et al 2018;Zimbres et al 2018;Gauthier et al 2019;Ilha et al 2019;Klarenberg et al 2019). In soybeans alone, Brazil increased its gross production by 94% between 1991 and 2013 (FAO 2016).…”

Section: Introductionmentioning

confidence: 99%

Deciphering the many maps of the Xingu – an assessment of land cover classifications at multiple scales

Kalácska

Arroyo‐Mora

Lucanus

et al. 2019

Preprint

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Remote sensing is an invaluable tool to objectively illustrate the rapid decline in habitat extents worldwide. Over the years, diverse Earth Observation platforms have been used to generate land cover maps, each with its unique characteristics. In addition, considerable semantic differences between the definition of land cover classes results in inevitable differences in baseline estimates for each class (e.g. forest). Here we compare forest cover and surface water estimates over four time periods spanning three decades for the Xingu River basin, Brazil, from pre-existing remotely sensed classifications for this area based on both optical and radar data. Because forest health in this area is directly related with the health of the freshwater ecosystem, we illustrate potential impacts of map choice on conservation of fish fauna. Understanding differences between the many remotely sensed baselines is fundamentally important to avoid information misuse and objectively decide on the most appropriate dataset for each conservation or policy making question. Our findings demonstrate the importance of transparency in the generation of remotely sensed datasets and in the importance of users familiarizing themselves with the characteristics and limitations of each data set chosen.

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“…It is also worth mentioning the Jequitinhonha River, which is born in the Serra do Espinhaço, in Serro, and travels a great distance until its mouth in the Atlantic Ocean [21]. Figure 1 presents a satellite view of the Minas Gerais territory, highlighting the main rivers and hydroelectric plants present in the territory.…”

Section: Minas Gerais Statementioning

confidence: 99%

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

2019

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Featured Application: A hybrid model formed by neural network techniques and fuzzy systems that predicts rainfall and temperatures in the capital of Minas Gerais, Brazil, which contains several river sources essential for the Brazilian economy. The purpose of the paper is to construct a model capable of extracting knowledge from satellite data related to temperatures and rainfall forecast of the analyzed state.Abstract: The forecast for rainfall and temperatures in underdevelope countries can help in the definition of public and private investment strategies in preventive and corrective nature. Water is an essential element for the economy and living things. This study had a main objective to use an intelligent hybrid model capable of extracting fuzzy rules from a historical series of temperatures and rainfall indices of the state of Minas Gerais in Brazil, more specifically in the capital. Because this is state has several rivers fundamental to the Brazilian economy, this study intended to find knowledge in the data of the problem to help public managers and private investors to act dynamically in the prediction of future temperatures and how they can interfere in the decisions related to the population of the state. The results confirm that the intelligent hybrid model can act with efficiency in the generation of predictions about the temperatures and average rainfall indices, being an efficient tool to predict the water situation in the future of this critical state for Brazil. Appl. Sci. 2019, 9, 5476 2 of 30 watersheds critical nationally. Along with several great cities, it has suffered a strong impact from drought [4].In contrast to the lack of water, it has problems with excess: floods and landslides [2]. If a river or stream receives a considerable amount of water from rain and cannot support it, it ends up overflowing and causing floods, which bring with it destruction, damage, and even death.The facts cited above are just some of the impacts that rain has on society. Within this context, this work was developed for the use of neural networks in the forecast of volumetric rainfall, based on a fuzzy rule system, developing a precise forecast, and contributing to the anticipation of possible tragedies s in places that occur phenomena of greater magnitude, as well as helping in a better control of agriculture. Another purpose was to support air and sea transportation, avoiding accidents in their trajectories. Briefly, when anticipating a possible problem, it is also possible to anticipate solutions and reduce their impacts, such as evacuating areas at risk of landslides or flooding [5].Currently, many kinds of research are being developed to apply models of artificial neural networks in rain forecasts, river basins, and water studies. For example, it was applied to the problem of forecasting the flow of the Nile River in Egypt [6], using a temporal series as a reference to compare tests among several prediction methods of neural networks. Besides, there was a study using stochastic autoregressive mean m...

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Impacts of tropical forest cover on water quality in agricultural watersheds in southeastern Brazil

Cited by 84 publications

References 37 publications

Agriculture influences ammonium and soluble reactive phosphorus retention in South American headwater streams

Agriculture influences ammonium and soluble reactive phosphorus retention in South American headwater streams

Deciphering the many maps of the Xingu – an assessment of land cover classifications at multiple scales

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

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