Cautioning against overemphasis of normative constructs in conservation decision making

Questions around how to conserve nature are increasingly leading to dissonance in conservation planning and action. While science can assist in unraveling the nature of conservation challenges, conservation responses rely heavily on normative positions and constructs to order actions, aid interpretations, and provide motivation. However, problems can arise when norms are mistaken for science or when they stymy scientific rigor. To highlight these potential pitfalls, we used the ethics-based tool of argument analysis to assess a controversial conservation intervention, the Pelorus Island Goat Control Program. The program proponents' argument for restorative justice was unsound because it relied on weak logical construction overly entrenched in normative assumptions. Overreliance on normative constructs, particularly the invocation of tragedy, creates a sense of urgency that can subvert scientific and ethical integrity, obscure values and assumptions, and increase the propensity for flawed logic. This example demonstrates how the same constructs that drive biodiversity conservation can also drive poor decision making, spur public backlash, and justify poor animal welfare outcomes. To provide clarity, a decision-making flowchart we devised demonstrates how values, norms, and ethics influence one another. We recommend practitioners follow 3 key points to improve decision making: be aware of values, as well as normative constructs and ethical theories that those values inform; be mindful of overreliance on either normative constructs or ethics when deciding action is justified; and be logically sound and transparent when building justifications. We also recommend 5 key attributes that practitioners should be attentive to when making conservation decisions: clarity, transparency, scientific integrity, adaptiveness, and compassion. Greater attention to the role of norms in decision making will improve conservation outcomes and garner greater public support for actions.     

Using social media images to assess ecosystem services in a remote protected area in the Argentinean Andes

Ambio - Social media images are a novel source of data to assess how people view and value the environment. Access to these images is often free, the volume and spread of images is expanding...     

Historical carbon fluxes in the expanding deforestation frontier of Southern Brazilian Amazonia (1985–2012)

In tropical areas, pioneer occupation fronts steer the rapid expansion of deforestation, contributing to carbon emissions. Up-to-date carbon emission estimates covering the long-term development of such frontiers depend on the availability of high spatial–temporal resolution data. In this paper, we provide a detailed assessment of carbon losses from deforestation and potential forest degradation from fragmentation for one expanding frontier in the Brazilian Amazon. We focused on one of the Amazonia’s hot-spots of forest loss, the BR-163 highway that connects the high productivity agricultural landscapes in Mato Grosso with the exporting harbors of the Amazon. We used multi-decadal (1984–2012) Landsat-based time series on forested and non-forested area in combination with a carbon book-keeping model. We show a 36% reduction in 1984s biomass carbon stocks, which led to the emission of 611.5 TgCO₂ between 1985 and 1998 (43.6 TgCO₂ year⁻¹) and 959.8 TgCO₂ over 1999–2012 (68.5 TgCO₂ year⁻¹). Overall, fragmentation-related carbon losses represented 1.88% of total emissions by 2012, with an increasing relevance since 2004. We compared the Brazilian Space Agency deforestation assessment (PRODES) with our data and found that small deforestation polygons not captured by PRODES had increasing importance on estimated deforestation carbon losses since 2000. The comparative analysis improved the understanding of data-source-related uncertainties on carbon estimates and indicated disagreement areas between datasets that could be subject of future research. Furthermore, spatially explicit, annual deforestation and emission estimates like the ones derived from this study are important for setting regional baselines for REDD+ or similar payment for ecosystem services frameworks.

     

High concentrations of polybrominated diphenylethers (PBDEs) in breast adipose tissue of California women

We measured major PBDEs and PCBs in breast adipose tissues of California women participating in a breast cancer study in the late 1990s. Samples were analyzed using gas chromatography with electron impact ionization and tandem mass spectrometry detection. The congener profile observed was: BDE47>BDE99>BDE153>BDE100>BDE154 and PCB153>PCB180>PCB138>PCB118. Whereas high correlations were observed within each chemical class, very weak correlations appeared between classes, pointing to different exposure pathways. Weak negative associations were observed for PBDE congeners and age. Our PBDE data are among the highest reported, exceeding data from the National Health and Nutrition Examination Survey and consistent with the high use of PBDEs in California. These data may be helpful in establishing a baseline for PBDE body burdens to gauge changes over time as a result of restrictions in the use of PBDE formulations.     

Dimethoate induces genotoxicity as a result of oxidative stress: in vivo and in vitro studies

Environmental Science and Pollution Research - Dimethoate ([O,O-dimethyl S-(N-methylcarbamoylmethyl) phosphorodithioate]) is an organophosphate insecticide and acaricide widely used for...     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

Integrated biological responses of zebrafish (Danio rerio) to analyze water quality in regions under anthropogenic influence

This study analyzed water quality in regions around Patos lagoon (Southern Brazil) that are under anthropogenic pressure. Water samples were collected from five different sites, including one used as a source for human consumption (COR) and others known to be influenced by human activities (IP). Danio rerio (Teleostei, Cyprinidae) organisms were exposed for 24 h to these water samples, plus a control group. It was observed that: (1) reactive oxygen species levels were lower in COR and IP than in the control group; (2) glutamate-cysteine ligase (catalytic subunit) expression was higher in COR than in other sites; (3) exposure to all water samples affected long-term memory (LTM) when compared to control group. Thus, some water samples possess the ability to modulate the antioxidant system and to induce a decline in cognitive functions, as measured by LTM. The obtained results indicate that a combination of variables of different organization level (molecular, biochemical and behavioral) can be employed to analyze water quality in impacted regions.     

An Analysis of Ozone Generation in Irradiated Houston Air

Ambient ozone measurements in the United States and many other countries are traceable to a National Institute of Standards and Technology Standard Reference Photometer (NIST SRP). The NIST SRP serves as the highest level ozone reference standard in the United States, with NIST SRPs located at NIST and at many U.S. Environmental Protection Agency (EPA) laboratories. The International Bureau of Weights and Measures (BIPM) maintains a NIST SRP as the reference standard for international measurement comparability through the International Committee of Weights and Measures (CIPM). In total, there are currently NIST SRPs located in 20 countries for use as an ozone reference standard. A detailed examination of the NIST SRP by the BIPM and NIST has revealed a temperature gradient and optical path-length bias inherent in all NIST SRPs. A temperature gradient along the absorption cells causes incorrect temperature measurements by as much as 2 °C. Additionally, the temperature probe used for temperature measurements was found to inaccurately measure the temperature of the sample gas due to a self-heating effect. Multiple internal reflections within the absorption cells produce an actual path length longer than the measured fixed length used in the calculations for ozone mole fractions. Reflections from optical filters located at the exit of the absorption cells add to this effect. Because all NIST SRPs are essentially identical, the temperature and path-length biases exist on all units by varying amounts dependent upon instrument settings, laboratory conditions, and absorption cell window alignment. This paper will discuss the cause of, and physical modifications for, reducing these measurement biases in NIST SRPs. Results from actual NIST SRP bias upgrades quantifying the effects of these measurement biases on ozone measurements are summarized.

Implications: NIST SRPs are maintained in laboratories around the world underpinning ozone measurement calibration and traceability within and between countries. The work described in this paper quantifies and shows the reduction of instrument biases in NIST SRPs improving their overall agreement. This improved agreement in all NIST SRPs provides a more stable baseline for ozone measurements worldwide.