Evaluation of Agricultural Land Cover Representations on Regional Climate Model Simulations in the Brazilian Cerrado

Examining interactions between large-scale land cover and land use change and regional climate in areas undergoing dynamic land transformations, like the Brazilian Cerrado, is crucial for understanding tradeoffs between human needs and ecosystem services. Yet regional climate models often do not include accurate land cover data of these complex landscapes. We use National Center for Atmospheric Research’s Weather Research and Forecasting (WRF) model coupled to the Noah-Multiparameterization (Noah-MP) land surface model to run 10-year climate simulations across Brazil to assess (1) whether an accurate, regionally validated land cover data set with two, new agricultural land cover classifications improves model simulation results; (2) the ability of Noah-MP’s dynamic vegetation option to model vegetation growth; and (3) the sensitivity of the model output to scale. The results of the simulations with the updated land surface perform better over intensive agricultural areas for precipitation, evapotranspiration, and temperature, especially during the wet-to-dry season transition months. Evapotranspiration is overestimated during the start of the rainy season across all model simulations, which is likely due to the soil moisture model. We also find that using the Noah-MP dynamic vegetation significantly degrades agricultural leaf area index phenology simulations in Brazilian agricultural regions. Lastly, improving the model’s resolution did not improve model output when compared to observational data. Incorporating more accurate representations of the landscape into regional climate models is essential for quantifying potential changes in climatological seasonality in dynamic, human-modified regions and making informed land use decisions

Bayes and Big Data: The Consensus Monte Carlo Algorithm

A useful definition of ‘big data’ is data that is too big to process comfortably on a single machine, either because of processor, memory, or disk bottlenecks. Graphics processing units can alleviate the processor bottleneck, but memory or disk bottlenecks can only be eliminated by splitting data across multiple machines. Communication between large numbers of machines is expensive (regardless of the amount of data being communicated), so there is a need for algorithms that perform distributed approximate Bayesian analyses with minimal communication. Consensus Monte Carlo operates by running a separate Monte Carlo algorithm on each machine, and then averaging individual Monte Carlo draws across machines. Depending on the model, the resulting draws can be nearly indistinguishable from the draws that would have been obtained by running a single-machine algorithm for a very long time. Examples of consensus Monte Carlo are shown for simple models where single-machine solutions are available, for large single-layer hierarchical models, and for Bayesian additive regression trees (BART)

Land cover classification using multi-temporal MERIS vegetation indices

The spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping. Moreover, two novel and operational vegetation indices derived from MERIS data have considerable potential as discriminating variables in land cover classification. Here, the potential of these two vegetation indices (the MERIS global vegetation index (MGVI), MERIS terrestrial chlorophyll index (MTCI)) was evaluated for mapping eleven broad land cover classes in Wisconsin. Data acquired in the high and low chlorophyll seasons were used to increase inter-class separability. The two vegetation indices provided a higher degree of inter-class separability than data acquired in many of the individual MERIS spectral wavebands. The most accurate landcover map (73.2%) was derived from a classification of vegetation index-derived data with a support vector machine (SVM), and was more accurate than the corresponding map derived from a classification using the data acquired in the original spectral wavebands

Emergency Wildlife Management Response to Protect Evidence Associated with the Terrorist Attack on the World Trade Center, New York City

At the request of the New York City Police Department, the PoIt Authority of New York and New Jersey, and the New York State Department of Environmental Conservation, a team of USDA APHIS Wildlife Services (WS) biologists mobilized in less than 24 hours to assist federal, state and local law enforcement officials in managing birds and rodents impacting the recovey of evidence as a result of the September 11, 2001 terrorist attacks on the World Trade Center. During the 10-month recovery effort fiom September 2001 to June 2002, more than 1.7 million tons of debris was shipped fiom Ground Zero in Manhatran to a high-security crime scene at the Fresh W s Landfill (FKL), Staten Island, New York Close to a billion pieces of debris were sorted by law enforcement officials to recover personal effects, human remains, and other evidence to document the crime and identlfy victims, as part of the largest forensic investigation in U.S. history. Within days of bringing debris to FKL, more than 2,600 gulls were on site, disrupting work of law enforcement officials and creating a concem that evidence would be lost to birds. Historically, FKL has been a feeding and loafmg site for over 100,000 gulls. To address this unprecedented wildlife damage management problem, WS implemented an integrated bud and rodent management program that involved 69 biologists from 23 states. The goal was to reduce the impact of pus, crows, house mice, and Norway rats on law enforcement personnel, equipment, and evidence collection including a zero-tolerance policy for gulls and crows landing on the working face. A combination of population surveys and direct management activities targeting gulls and crows was initiated 12-14 hours a day, 7 days a week using visual and noise deterrents including pyrotechnics, mylar tape, human and dead-bud effigies, lasers, paint ball guns, and lethal removal of a limited number of birds. In addition, commensal rodent surveys with snap traps were conducted twice monthly to document population trends and explore the need for rodent control on site. We deployed over 23,000 pyrotechnics and dispased over 172,000 gulls and 5,000 crows fiom the site. We removed 293 house mice and 46 Norway rats in 6,000 trapnights. \u27Ibe program was highly effective in preventing gulls and crows from feeding on remains and disrupting workers. We discuss other key lessons learned regarding an emergency response program to manage wildlife

Emergency Wildlife Management Response to Protect Evidence Associated with the Terrorist Attack on the World Trade Center, New York City

At the request of the New York City Police Department, the PoIt Authority of New York and New Jersey, and the New York State Department of Environmental Conservation, a team of USDA APHIS Wildlife Services (WS) biologists mobilized in less than 24 hours to assist federal, state and local law enforcement officials in managing birds and rodents impacting the recovey of evidence as a result of the September 11, 2001 terrorist attacks on the World Trade Center. During the 10-month recovery effort fiom September 2001 to June 2002, more than 1.7 million tons of debris was shipped fiom Ground Zero in Manhatran to a high-security crime scene at the Fresh W s Landfill (FKL), Staten Island, New York Close to a billion pieces of debris were sorted by law enforcement officials to recover personal effects, human remains, and other evidence to document the crime and identlfy victims, as part of the largest forensic investigation in U.S. history. Within days of bringing debris to FKL, more than 2,600 gulls were on site, disrupting work of law enforcement officials and creating a concem that evidence would be lost to birds. Historically, FKL has been a feeding and loafmg site for over 100,000 gulls. To address this unprecedented wildlife damage management problem, WS implemented an integrated bud and rodent management program that involved 69 biologists from 23 states. The goal was to reduce the impact of pus, crows, house mice, and Norway rats on law enforcement personnel, equipment, and evidence collection including a zero-tolerance policy for gulls and crows landing on the working face. A combination of population surveys and direct management activities targeting gulls and crows was initiated 12-14 hours a day, 7 days a week using visual and noise deterrents including pyrotechnics, mylar tape, human and dead-bud effigies, lasers, paint ball guns, and lethal removal of a limited number of birds. In addition, commensal rodent surveys with snap traps were conducted twice monthly to document population trends and explore the need for rodent control on site. We deployed over 23,000 pyrotechnics and dispased over 172,000 gulls and 5,000 crows fiom the site. We removed 293 house mice and 46 Norway rats in 6,000 trapnights. \u27Ibe program was highly effective in preventing gulls and crows from feeding on remains and disrupting workers. We discuss other key lessons learned regarding an emergency response program to manage wildlife

Emergency Wildlife Management Response to Protect Evidence Associated with the Terrorist Attack on the World Trade Center, New York City

At the request of the New York City Police Department, the PoIt Authority of New York and New Jersey, and the New York State Department of Environmental Conservation, a team of USDA APHIS Wildlife Services (WS) biologists mobilized in less than 24 hours to assist federal, state and local law enforcement officials in managing birds and rodents impacting the recovey of evidence as a result of the September 11, 2001 terrorist attacks on the World Trade Center. During the 10-month recovery effort fiom September 2001 to June 2002, more than 1.7 million tons of debris was shipped fiom Ground Zero in Manhatran to a high-security crime scene at the Fresh W s Landfill (FKL), Staten Island, New York Close to a billion pieces of debris were sorted by law enforcement officials to recover personal effects, human remains, and other evidence to document the crime and identlfy victims, as part of the largest forensic investigation in U.S. history. Within days of bringing debris to FKL, more than 2,600 gulls were on site, disrupting work of law enforcement officials and creating a concem that evidence would be lost to birds. Historically, FKL has been a feeding and loafmg site for over 100,000 gulls. To address this unprecedented wildlife damage management problem, WS implemented an integrated bud and rodent management program that involved 69 biologists from 23 states. The goal was to reduce the impact of pus, crows, house mice, and Norway rats on law enforcement personnel, equipment, and evidence collection including a zero-tolerance policy for gulls and crows landing on the working face. A combination of population surveys and direct management activities targeting gulls and crows was initiated 12-14 hours a day, 7 days a week using visual and noise deterrents including pyrotechnics, mylar tape, human and dead-bud effigies, lasers, paint ball guns, and lethal removal of a limited number of birds. In addition, commensal rodent surveys with snap traps were conducted twice monthly to document population trends and explore the need for rodent control on site. We deployed over 23,000 pyrotechnics and dispased over 172,000 gulls and 5,000 crows fiom the site. We removed 293 house mice and 46 Norway rats in 6,000 trapnights. \u27Ibe program was highly effective in preventing gulls and crows from feeding on remains and disrupting workers. We discuss other key lessons learned regarding an emergency response program to manage wildlife

Bayesian Classification and Regression Trees for Predicting Incidence of Cryptosporidiosis

Background Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. Methodology/Principal Findings We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR) model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. Conclusions/Significance A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control

Synthesis of cyclic carbonates from CO2 and epoxides using ionic liquids and related catalysts including choline chloride–metal halide mixtures

In this mini-review, progress made in the use of ionic liquid catalysts and related systems for cycloaddition reactions of carbon dioxide with epoxides is described with the primary focus on results from the past eight years. Catalysts described range from simple onium species including tetrabutylammonium bromide, functionalized and simple imidazolium ionic liquids, to a plethora of supported ionic liquid systems. A range of supports including alumina, silica, carbon nanotubes, magnetic nanoparticles, poly(ethyleneglycol), polystyrene, cellulose and chitosan have been used with a variety of ionic groups. These include ammonium, phosphonium and both functionalized and unfunctionalized imidazolium salts. Results have been tabulated to summarize reaction conditions and TONs for styrene oxide, propylene oxide and cyclohexene oxide conversions. It is clear that metal ions used in combination with ionic liquids, particularly ZnBr2, can enhance conversions, and hydroxyl, carboxyl and other functional groups capable of hydrogen-bonding can be incorporated to improve catalysis. Some recent results using flow reactors are highlighted. Examples of ionic catalysts used in the related processes of oxidative carboxylation of alkenes, which also yields cyclic carbonate products, and carbon dioxide–aziridine coupling reactions, which yield oxazolidinone products are described. New data on catalytic styrene carbonate production using choline chloride-transition metal chloride mixtures are presented. For 3d metals, the catalytic activity of these mixtures is Cr > Co ≈ Fe ≈ Ni > Mn ≫ Cu