Spatial distribution of pesticides,organochlorine compounds,PBDEs, and metals in surface marine sediments from Cartagena Bay,Colombia

Environmental Science and Pollution Research - Cartagena Bay is an estuarine system located in the Caribbean Sea (Colombia, South America), that receives fresh water from Canal del Dique, which is...     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

Urban wild meat consumption and trade in central Amazonia

The switch from hunting wild meat for home consumption to supplying more lucrative city markets in Amazonia can adversely affect some game species. Despite this, information on the amounts of wild meat eaten in Amazonian cities is still limited. We estimated wild meat consumption rates in 5 cities in the State of Amazonas in Brazil through 1046 door-to-door household interviews conducted from 2004 to 2012. With these data, we modeled the relationship between wild meat use and a selection of socioeconomic indices. We then scaled up our model to determine the amounts of wild meat likely to be consumed annually in the 62 urban centers in central Amazonia. A total of 80.3% of all interviewees reported consuming wild meat during an average of 29.3 (CI 11.6) days per year. Most wild meat was reported as bought in local markets (80.1%) or hunted by a family member (14.9%). Twenty-one taxa were cited as consumed, mostly mammals (71.6%), followed by reptiles (23.2%) and then birds (5.2%). The declared frequency of wild meat consumption was positively correlated with the proportion of rural population as well as with the per capita gross domestic product of the municipality (administrative divisions) where the cities were seated. We estimated that as much as 10,691 t of wild meat might be consumed annually in the 62 urban centers within central Amazonia, the equivalent of 6.49 kg per person per year. In monetary terms, this amounts to US$21.72 per person per year or US$35.1 million overall, the latter figure is comparable to fish and timber production in the region. Given this magnitude of wild meat trade in central Amazonia, it is fundamental to integrate this activity into the formal economy and actively develop policies that allow the trade of more resilient taxa and restrict trade in species sensitive to hunting.     

Applying the zoo model to conservation of threatened exceptional plant species

Maintaining a living plant collection is the most common method of ex situ conservation for plant species that cannot be seed banked (i.e., exceptional species). Viability of living collections, and their value for future conservation efforts, can be limited without coordinated efforts to track and manage individuals across institutions. Using a pedigree-focused approach, the zoological community has established an inter-institutional infrastructure to support long-term viability of captive animal populations. We assessed the ability of this coordinated metacollection infrastructure to support the conservation of 4 plant species curated in living collections at multiple botanic gardens around the world. Limitations in current practices include the inability to compile, share, and analyze plant collections data at the individual level, as well as difficulty in tracking original provenance of ex situ material. The coordinated metacollection framework used by zoos can be adopted by the botanical community to improve conservation outcomes by minimizing the loss of genetic diversity in collections. We suggest actions to improve ex situ conservation of exceptional plant species, including developing a central database to aggregate data and track unique individuals of priority threatened species among institutions and adapting a pedigree-based population management tool that incorporates life-history aspects unique to plants. If approached collaboratively across regional, national, and global scales, these actions could transform ex situ conservation of threatened plant species.     

The use of nanovermiculite catalyst in the study of removal of the organic load and degradation of atrazine via ozone process in RPB reactor

Abstract

The main objective of this study is the degradation of a synthetic solution of atrazine by a modified vermiculite catalyzed ozonation, in a rotating packed bed (RPB) reactor. A 0.5?L RPB reactor was used to perform the experiments, using a Central Composite Design (CCD) response surface to construct the quadratic model based on the factors: pH, catalyst concentration and reactor rotation frequency. The response variable was the removal of the organic load measured in terms of Chemical Oxygen Demand (COD). After the complete quadratic model was constructed through the response surface, the COD degradation process had an optimal removal of 41% under the following conditions: pH 8.0, rotation of 1150?rpm and catalyst concentration 0.66?g L^?1.     

Comparison between UVA- and zero-valent iron-activated persulfate processes for degrading propylparaben

Conventional wastewater treatments are not efficient in removing parabens, which may thus end up in surface waters, posing a threat to aquatic biota and hu     

The dual discourse of urban resilience: robust city and self-organised neighbourhoods

Resilience has become a dominant disaster governance discourse. It has been criticised for insufficiently addressing systemic vulnerabilities while urging the vulnerable to self-organise. The urban resilience discourse involves a particular disconnect: it evokes ‘robustness’ and unaffectedness at the city scale on the one hand, and self-organisation of disaster-affected people and neighbourhoods on the other. This paper explains and illustrates the dual discourse through a case study on the reconstruction of informal and low-income settlements in the aftermath of the fire in Valparaíso, Chile, in 2014, focusing on the communication contents of two non-governmental organisations (NGOs). These NGOs deployed the discourse differently, yet both called for affected neighbourhoods to build a more robust city through self-organisation, and both suggested their work as the missing link between self-organisation and robustness. A danger in deploying the dual discourse is that it requires people who live in informal and low-income settlements to earn their right to the robust city through ‘better’ self-organisation based on fragmented visions.     

Practitioner Insights into Weed Management on California’s Rangelands and Natural Areas

Working rangelands and natural areas span diverse ecosystems and face both ecological and economic threats from weed invasion. Restoration practitioners and land managers hold a voluminous cache of place-based weed management experience and knowledge that has largely been untapped by the research community. We surveyed 260 California rangeland managers and restoration practitioners to investigate invasive and weedy species of concern, land management goals, perceived effectiveness of existing practices (i.e., prescribed fire, grazing, herbicide use, and seeding), and barriers to practice implementation. Respondents identified 196 problematic plants, with yellow starthistle (Centaurea solstitialis L.) and medusahead (Elymus caput-medusae L.) most commonly listed. Reported adoption and effectiveness of weed management practices varied regionally, but the most highly rated practice in general was herbicide use; however, respondents identified considerable challenges including nontarget effects, cost, and public perception. Livestock forage production was the most commonly reported management goals (64% of respondents), and 25% of respondents were interested in additional information on using grazing to manage invasive and weedy species; however, 19% of respondents who had used grazing for weed management did not perceive it to be an effective tool. Across management practices, we also found common barriers to implementation, including operational barriers (e.g., permitting, water availability), potential adverse impacts, actual effectiveness, and public perception. Land manager and practitioner identified commonalities of primary weeds, management goals, perceived practice effectiveness, and implementation barriers across diverse bioregions highlight major needs that could be immediately addressed through management–science partnerships across the state’s expansive rangelands and natural areas.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.