“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.     

Habitat quality,not habitat amount,drives mammalian habitat use in the Brazilian Pantanal

Landscape Ecology - An understanding of species-habitat relationships is required to assess the impacts of habitat fragmentation and degradation. To date, habitat modeling in fragmented landscapes...     

Contrasting edge and pasture matrix effects on ant diversity from fragmented landscapes across multiple spatial scales

Landscape Ecology - Harmful effects of habitat loss and fragmentation can be detected across multiple spatial scales, yet most studies that aim to characterize these effects take place at a single...     

Landscape composition is the major driver of the taxonomic and functional diversity of tropical frugivorous birds

Landscape Ecology - Anthropogenic land use and cover changes impact biodiversity worldwide. However, ecological groups are differently affected by landscape composition and configuration....     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.     

PCB removal,soil enzyme activities,and microbial community structures during the phytoremediation by alfalfa in field soils

Purpose  

An in situ phytoremediation trial was developed in order to investigate the function of alfalfa during a 2-year bioremediation of an agricultural soil contaminated with polychlorinated biphenyls (PCBs). The study was conducted with the aim to better understand the application potential of PCB phytoremediation at field scale.     

Atmospheric Mercury Fluxes in a Southern Boreal Forest and Wetland

Total gaseous mercury (TGM) fluxes from the forest floor and a boreal wetland were measured by a flux chamber technique coupled with an automatic mercury vapour analyser. The fluxes were measured at three sampling sites in southern Finland, 61°14′ N, 25°04′ E in summer 2007, with additionally in situ TGM concentrations in the air at one of the sites and mercury bulk deposition at another. Most of the flux data were collected during the daytime. At one of the sites, diurnal flux behaviour was studied, and a clear cycle with an afternoon maximum and a night minimum was observed. The highest emissions (up to 3.5 ng m⁻² h⁻¹) were observed at the forest floor site having a moss and grass cover. At the wetland and litter-rich forest floor sites, the emissions were below 1 ng m⁻² h⁻¹ and sometimes negative (down to −1.0 ng m⁻² h⁻¹), indicating mercury uptake. The measured average fluxes in August were 0.9 ± 1.1 and 0.2 ± 0.3 ng m⁻² h⁻¹ for the forest floor sites and wetland sites, respectively. The flux data were compared with the mercury bulk deposition, which proved to be of the same magnitude, but opposite in sign. At the mossy forest floor site, the extrapolated TGM emissions were 130% of the Hg deposition in August 2007. Comparison with other studies showed that the fluxes in background areas are relatively uniform, regardless of measurement site location and method used. Airborne TGM remained at the background level during the study, with an average value of 1.3 ± 0.2 ng m⁻³; it frequently showed a diurnal cycle pattern.     

Interactive effects of Cd and PAHs on contaminants removal from co-contaminated soil planted with hyperaccumulator plant <Emphasis Type="Italic">Sedum alfredii</Emphasis>

Purpose  

Soil contamination by multiple organic and inorganic contaminants is common but its remediation by hyperaccumulator plants is rarely reported. The growth of a cadmium (Cd) hyperaccumulator Sedum alfredii and removal of contaminants from Cd and polycyclic aromatic hydrocarbons (PAHs) co-contaminated soil were reported in this study.     

Performance and Kinetic Study on Bioremediation of Diazo Dye (Reactive Black 5) in Wastewater Using Spent GAC–Biofilm Sequencing Batch Reactor

Combinations of sequential anaerobic and aerobic process enhance the treatment of textile wastewater. The aim of this study was to investigate the treatment of diazo dye Reactive Black 5 (RB5)-containing wastewater using granular activated carbon (GAC)–biofilm sequencing batch reactor (SBR) as an integration of aerobic and anaerobic process in a single reactor. The GAC–biofilm SBR system demonstrated higher removal of COD, RB5 and aromatic amines. It was observed that the RB5 removal efficiency improved as the concentration of co-substrate in the influent increased. The alternative aeration introduced into the bioreactor enhanced mineralization of aromatic amines. Degradation of RB5 and co-substrate followed second-order kinetic and the constant (k ₂) values for COD and RB5 decreased from 0.002 to 0.001 and 0.004 to 0.001 l/mg h, respectively, as the RB5 concentration increased from 100 to 200 mg/l in the GAC–biofilm SBR system.