The Relationship between Narratives,Wildlife Value Orientations,Attitudes, and Policy Preferences

Overabundance of white-tailed deer is a pervasive problem across the United States. Deer are blamed for increased risk of auto accidents, tick-borne diseases, and overbrowsing of native species. Lethal management techniques, cited as cost-effective and humane, are commonly employed for herd management. However, the approach frequently sparks outrage among various stakeholders who feel killing of animals is unjustified and prefer nonlethal measures. Wildlife managers then face the challenge of communicating with the public to build policy support for lethal management. The Narrative Policy Framework was used to test the effects of differing narratives on public opinion for lethal deer management. Results indicated narratives were influential in shifting attitudes toward and support for a proposed sharpshooting policy even in some cases where respondents were already familiar with the issue and held a previous opinion. This study also supported the utility of the Narrative Policy Framework for examining human dimensions of wildlife issues.     

The Symbolic Wolf: A Construal Level Theory Analysis of the Perceptions of Wolves in the United States

Charismatic wildlife can be difficult to manage due to the controversies they generate among stakeholders, which may be rooted in their symbolic meaning. Using construal-level theory, we coded the images of gray wolves mentioned by respondents to a national survey (n?=?621) and an issue public survey (n?=?447) as symbolic (abstract) or corporeal (concrete). We analyzed the relationship between these representations of wolves and several perceptions that may perpetuate social conflict. Most people thought of wolves abstractly, and abstract thoughts were associated with positive feelings toward wolves and agreement with existence beliefs regarding wolves. Concrete representations were associated with identifying as a gun or property rights advocate, hunter, or farmer/rancher. Given these disparate views of wolves, engaging stakeholders through collaborative processes designed to foster a shared understanding of this species, while addressing the concerns of those groups, could be useful in reducing conflict concerning wolf management.     

Surficial and Deep Earth Material Prediction from Geochemical Compositions

Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based on their contribution to the predictive model. To generate potential and uncertainty maps, compositional data are simulated at unsampled locations via a chain of transformations (isometric log-ratio transformation followed by the flow anamorphosis) and geostatistical simulation. The simulated results are subsequently back-transformed to the original compositional space. The trained predictive model is used to estimate the probability of classes for simulated compositions. The proposed approach is illustrated through two case studies. In the first case study, the major crustal blocks of the Australian continent are predicted from the surface regolith geochemistry of the National Geochemical Survey of Australia project. The aim of the second case study is to discover the superficial deposits (peat) from the regional-scale soil geochemical data of the Tellus Project. The accuracy of the results in these two case studies confirms the usefulness of the proposed method for geological class prediction and geological process discovery.

     

Same space – different perspectives: comparative analysis of geographic context through sketch maps and spatial video geonarratives

ABSTRACT

The importance of including a contextual underpinning to the spatial analysis of social data is gaining traction in the spatial science community. The challenge, though, is how to capture these data in a rigorous manner that is translational. One method that has shown promise in achieving this aim is the spatial video geonarrative (SVG), and in this paper we pose questions that advance the science of geonarratives through a case study of criminal ex-offenders. Eleven ex-offenders provided sketch maps and SVGs identifying high-crime areas of their community. Wordmapper software was used to map and classify the SVG content; its spatial filter extension was used for hot spot mapping with statistical significance tested using Monte Carlo simulations. Then, each subject’s sketch map and SVG were compared. Results reveal that SVGs consistently produce finer spatial-scale data and more locations of relevance than the sketch maps. SVGs also provide explanation of spatial-temporal processes and causal mechanisms linked to specific places, which are not evident in the sketch maps. SVG can be a rigorous translational method for collecting data on the geographic context of many phenomena. Therefore, this paper makes an important advance in understanding how environmentally immersive methods contribute to the understanding of geographic context.     

Spatiotemporal aspects of silica buffering in restored tidal marshes

Losses of pelagic diatom production resulting from silica limitation have not only been blamed for toxic algal blooms, but for the reduction in ability of coastal food webs to support higher trophic levels. Recent research has shown the importance of advective seepage water fluxes of dissolved silica (DSi) from freshwater marshes to pelagic waters during moments of riverine Si-limitation. In this study, we investigated the potential impact of recently installed new tidal areas along the Schelde estuary, located in former polder areas and characterized by so-called controlled reduced tidal regimes (CRT). Nine mass-balance studies were conducted in a newly constructed CRT in the freshwater Schelde estuary. During complete tidal cycles both DSi and amorphous silica (ASi) concentrations were monitored at the entrance culverts and in different habitats in the marsh. A swift DSi-delivery capacity was observed despite the shifted spatiotemporal frame of exchange processes compared to reference marshes. As silica-accumulating vegetation is not yet present, and difference with reference marshes’ deliveries is surprisingly small, we indicate diatomaceous debris and phytoliths to be the main silica source. Although further research is necessary on the driving forces of the different processes involved, restoration of former agricultural areas under CRT-regime provide the potential to buffer silica in the estuary.     

Shark interactions in pelagic longline fisheries

Substantial ecological, economic and social problems result from shark interactions in pelagic longline fisheries. Improved understanding of industry attitudes and practices towards shark interactions assists with managing these problems. Information on fisher knowledge and new strategies for shark avoidance may benefit sharks and fishers. A study of 12 pelagic longline fisheries from eight countries shows that incentives to avoid sharks vary along a continuum, based on whether sharks represent an economic disadvantage or advantage. Shark avoidance practices are limited, including avoiding certain areas, moving when shark interaction rates are high, using fish instead of squid for bait and deeper setting. Some conventionally employed fishing gear and methods used to target non-shark species contribute to shark avoidance. Shark repellents hold promise; more research and development is needed. Development of specifically designed equipment to discard sharks could improve shark post release survival prospects, reduce gear loss and improve crew safety. With expanding exploitation of sharks for fins and meat, improved data collection, monitoring and precautionary shark management measures are needed to ensure that shark fishing mortality levels are sustainable.     

Seasonal variation of eddy shedding from the Kuroshio intrusion in the Luzon Strait

Altimeter data and output from the HYbrid Coordinate Ocean Model global assimilation run are used to study the seasonal variation of eddy shedding from the Kuroshio intrusion in the Luzon Strait. The results suggest that most eddy shedding events occur from December through March, and no eddy shedding event occurs in June, September, or October. About a month before eddy shedding, the Kuroshio intrusion extends into the South China Sea and a closed anticyclonic eddy appears inside the Kuroshio loop which then detaches from the Kuroshio intrusion. Anticyclonic eddies detached from December through February move westward at a speed of about 0.1 m s⁻¹ after shedding, whereas eddies detached in other months either stay at the place of origin or move westward at a very slow speed (less than 0.06 m s⁻¹). The HYCOM outputs and QuikSCAT wind data clearly show that the seasonal variation of eddy shedding is influenced by the monsoon winds. A comparison between eddy volume and integrated Ekman transport indicates that, once the integrated Ekman transport exceeds 2 × 10¹² m³ (which roughly corresponds to the volume of an eddy), the Kuroshio intrusion expands and an eddy shedding event occurs within 1 month. We infer that the Ekman drift of the northeasterly monsoon pushes the Kuroshio intrusion into the SCS, creates a net westward transport into the Strait, and leads to an eddy detachment from the Kuroshio.     

Numerical modeling of nonlinear water waves over heterogeneous porous beds

The transformation of nonlinear water waves over porous beds is studied by applying a numerical model based on Chen's [2006. Fully nonlinear Boussinesq-type equations for waves and currents over porous beds. Journal of Engineering Mechanics, 132:2, 220–230] Boussinesq-type equations for highly nonlinear waves on permeable beds. The numerical model uses a high-order time-marching solution and fourth-order finite-difference schemes for discretization of first-order spatial derivatives to obtain a computational accuracy consistent with the model equations. By forcing the wave celerity and spatial porous-damping rate of the linearized model to match the exact linear theory for horizontal porous bed over a prescribed range of relative depths, the values of the model parameters are optimally determined. Numerical simulations of the damped wave propagation over finite-thickness porous layer demonstrate the accuracy of both the numerical model and governing equations, which have been shown by prior theoretical analyses to be accurate for both nominal and thick porous layers. These simulations also elucidate on the significance of the higher-order porous-damping terms and the influence of the hydraulic parameters. Application of the model to the simulation of the wave field around a laboratory-scale submerged porous mound provides a measure of its capability, as well as useful insight into the scaling of the porous-resistance coefficients. For application to heterogeneous porous beds, the assumption of weak spatial variation of the porous resistance is examined using truncated forms of the governing equations. The results indicate that the complete set of Boussinesq-type equations is applicable to porous beds of nonhomogeneous makeup.     

Why chromatic imaging matters

During the last two decades, the first generation of beam combiners at the Very Large Telescope Interferometer has proved the importance of optical interferometry for high-angular resolution astrophysical studies in the near- and mid-infrared. With the advent of 4-beam combiners at the VLTI, the u ? v coverage per pointing increases significantly, providing an opportunity to use reconstructed images as powerful scientific tools. Therefore, interferometric imaging is already a key feature of the new generation of VLTI instruments, as well as for other interferometric facilities like CHARA and JWST. It is thus imperative to account for the current image reconstruction capabilities and their expected evolutions in the coming years. Here, we present a general overview of the current situation of optical interferometric image reconstruction with a focus on new wavelength-dependent information, highlighting its main advantages and limitations. As an Appendix we include several cookbooks describing the usage and installation of several state-of-the art image reconstruction packages. To illustrate the current capabilities of the software available to the community, we recovered chromatic images, from simulated MATISSE data, using the MCMC software SQUEEZE. With these images, we aim at showing the importance of selecting good regularization functions and their impact on the reconstruction.