ASSESSING THE LOUISIANA SHRIMP FISHING FLEET TECHNICAL EFFICIENCY USING A BAYESIAN STOCHASTIC COST FRONTIER MODEL

A Bayesian stochastic cost frontier analyzed the shrimp fleet of Louisiana. A translog cost function was estimated. 269 vessels were included and sub-grouped by length (<20 ft, 21-40ft, and >60ft), and net type (trawl, skimmer, and butterfly). Results indicated no influence of these factors on cost efficiency.Resource /Energy Economics and Policy,

IRRIGATION AND POTENTIAL DIVERSIFICATION BENEFITS IN HUMID CLIMATES

Income variability and means for managing risk continue to receive much attention in farm management research. In this paper, irrigation is presented as a risk-management strategy that offers potential diversification benefits. Potential diversification opportunities largely result from a wider range of enterprise production activities. A portfolio analysis of dryland and irrigated farm scenarios indicates that income stabilizing and diversification effects of irrigation substantially modify the risk-return position of a typical farm in northeast Louisiana. Safety-first considerations along with Target MOTAD programming procedures also are used to evaluate the impact of irrigation on the farm's financial performance.Farm Management,

A DOUBLE HURDLE APPROACH TO EVALUATING NON-RESIDENTIAL WILDLIFE WATCHING IN THE UNITED STATES

In 1996, over 62 million U.S. residents participated in wildlife watching and spent in excess of 29 billion dollars in this recreational activity. Wildlife watching can be defined as the observation, study, and enjoyment of natural areas and its wild fauna and flora. Residential wildlife watching takes place within one mile of the participant's residence and is often an incidental or secondary activity. Non-residential wildlife watching refers to recreation taking place at a distance of at least one mile from the participant's residence. In recent years, a sharp decline in the number of wildlife watchers has been noted. Between 1991 and 1996, the number of wildlife watchers decreased by 17 percent. During this time interval, the largest decline in participation was observed in non-residential viewing. The number of non-residential wildlife watchers declined by 21 percent. This trend is damaging to towns and communities, especially rural communities which largely depend on recreation dollars. The mitigation or reversal of this trend hinges upon the identification of factors affecting participation and expenditures on wildlife viewing. The determining role of several socioeconomic attributes in explaining participation and expenditures on nature-related recreation has been widely studied in the leisure and recreation literature. However, most of these past studies have focused on fishing and hunting activities rather than the equally important non-residential wildlife watching. Hence, this study evaluates participation decisions and the extent of the participation in non-residential wildlife watching in the United States. Keywords: wildlife watching, limited dependent variables, double hurdlewildlife watching, limited dependent variables, double hurdle, Resource /Energy Economics and Policy,

Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions

We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations for the Arctic during summer. The products are compared against SIC and net ice surface fraction (ISF) - SIC minus the per-grid-cell melt pond fraction (MPF) on sea ice - as derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations and observed from ice-going vessels. Like in Kern et al. (2019), we group the 10 products based on the concept of the SIC retrieval used. Group I consists of products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms. Group II consists of products derived with the Comiso bootstrap algorithm and the National Oceanographic and Atmospheric Administration (NOAA) National Snow and Ice Data Center (NSIDC) SIC climate data record (CDR). Group III consists of Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) and National Aeronautics and Space Administration (NASA) Team (NT) algorithm products, and group IV consists of products of the enhanced NASA Team algorithm (NT2). We find widespread positive and negative differences between PMW and MODIS SIC with magnitudes frequently reaching up to 20 %-25 % for groups I and III and up to 30 %-35 % for groups II and IV. On a pan-Arctic scale these differences may cancel out: Arctic average SIC from group I products agrees with MODIS within 2 %-5 % accuracy during the entire melt period from May through September. Group II and IV products overestimate MODIS Arctic average SIC by 5 %-10 %. Out of group III, ASI is similar to group I products while NT SIC underestimates MODIS Arctic average SIC by 5 %-10 %. These differences, when translated into the impact computing Arctic sea-ice area (SIA), match well with the differences in SIA between the four groups reported for the summer months by Kern et al. (2019). MODIS ISF is systematically overestimated by all products; NT provides the smallest overestimations (up to 25 %) and group II and IV products the largest overestimations (up to 45 %). The spatial distribution of the observed overestimation of MODIS ISF agrees reasonably well with the spatial distribution of the MODIS MPF and we find a robust linear relationship between PMW SIC and MODIS ISF for group I and III products during peak melt, i.e. July and August. We discuss different cases taking into account the expected influence of ice surface properties other than melt ponds, i.e. wet snow and coarse-grained snow/refrozen surface, on brightness temperatures and their ratios used as input to the SIC retrieval algorithms. Based on this discussion we identify the mismatch between the actually observed surface properties and those represented by the ice tie points as the most likely reason for (i) the observed differences between PMW SIC and MODIS ISF and for (ii) the often surprisingly small difference between PMW and MODIS SIC in areas of high melt pond fraction. We conclude that all 10 SIC products are highly inaccurate during summer melt. We hypothesize that the unknown number of melt pond signatures likely included in the ice tie points plays an important role - particularly for groups I and II - and recommend conducting further research in this field

Analysis of hepatitis C virus RNA dimerization and core–RNA interactions

The core protein of hepatitis C virus (HCV) has been shown previously to act as a potent nucleic acid chaperone in vitro, promoting the dimerization of the 3′-untranslated region (3′-UTR) of the HCV genomic RNA, a process probably mediated by a small, highly conserved palindromic RNA motif, named DLS (dimer linkage sequence) [G. Cristofari, R. Ivanyi-Nagy, C. Gabus, S. Boulant, J. P. Lavergne, F. Penin and J. L. Darlix (2004) Nucleic Acids Res., 32, 2623–2631]. To investigate in depth HCV RNA dimerization, we generated a series of point mutations in the DLS region. We find that both the plus-strand 3′-UTR and the complementary minus-strand RNA can dimerize in the presence of core protein, while mutations in the DLS (among them a single point mutation that abolished RNA replication in a HCV subgenomic replicon system) completely abrogate dimerization. Structural probing of plus- and minus-strand RNAs, in their monomeric and dimeric forms, indicate that the DLS is the major if not the sole determinant of UTR RNA dimerization. Furthermore, the N-terminal basic amino acid clusters of core protein were found to be sufficient to induce dimerization, suggesting that they retain full RNA chaperone activity. These findings may have important consequences for understanding the HCV replicative cycle and the genetic variability of the virus

‘In the dark’: Voices of parents in marginalised stepfamilies: perceptions and experiences of their parenting support needs

The fastest growing family type in the UK is the stepfamily with social parenting an increasingly normal practice. Parenting policy and practice, which has increased exponentially over the last two decades, has historically been modelled on the biological nuclear family model with marginalised families the main recipients. The possibility that parents in marginalised stepfamilies might have separate and discrete parenting support needs to biological parents seems to be overlooked in policy, practice and research. Rather, the historical legacy of deficit, dysfunction and a ‘whiff’ of poor parenting in marginalised stepfamilies lingers on. The focus of the research was to determine marginalised parents’ perceptions and experiences of parenting in their stepfamily and their parenting support needs. Thematic analysis of the data revealed accounts that were interwoven throughout with strong moral undertones which seemed to categorise their lives. The parenting issues were different and more complex than those they had encountered before. The parents adopted biological family identities, but these didn’t fit with their social roles and often rendered them powerless in their relationships with stepchildren. This appeared to have a cumulative effect which impacted on the already fragile couple relationship. Despite the parents easy articulation of the parenting issues there was a contrasting unease and ambivalence in discussing parenting support needs. Parenting support seemed to be an irrelevance that could be disregarded. Ultimately the moral significance of the parents marginalised class positions appeared to be central to their lives, which has important implications for policy and practice

Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations

We report on results of a systematic intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution for both the Arctic and the Antarctic. The products are compared with each other with respect to differences in SIC, sea-ice area (SIA), and sea-ice extent (SIE), and they are compared against a global wintertime near-100 % reference SIC data set for closed pack ice conditions and against global year-round ship-based visual observations of the sea-ice cover. We can group the products based on the concept of their SIC retrieval algorithms. Group I consists of data sets using the self-optimizing EUMETSAT OSI SAF and ESA CCI algorithms. Group II includes data using the Comiso bootstrap algorithm and the NOAA NSIDC sea-ice concentration climate data record (CDR). The standard NASA Team and the ARTIST Sea Ice (ASI) algorithms are put into group III, and NASA Team 2 is the only element of group IV. The three CDRs of group I (SICCI-25km, SICCI-50km, and OSI-450) are biased low compared to a 100 % reference SIC data set with biases of - 0.4 % to -1.0 % (Arctic) and -0.3 % to -1.1 % (Antarctic). Products of group II appear to be mostly biased high in the Arctic by between +1.0 % and +3.5 %, while their biases in the Antarctic range from -0.2 % to +0.9 %. Group III product biases are different for the Arctic, +0.9 % (NASA Team) and -3.7 % (ASI), but similar for the Antarctic, -5.4 % and -5.6 %, respectively. The standard deviation is smaller in the Arctic for the quoted group I products (1.9 % to 2.9 %) and Antarctic (2.5 % to 3.1 %) than for group II and III products: 3.6 % to 5.0 % for the Arctic and 4.0 % to 6.5 % for the Antarctic. We refer to the paper to understand why we could not give values for group IV here. We discuss the impact of truncating the SIC distribution, as naturally retrieved by the algorithms around the 100 % sea-ice concentration end. We show that evaluation studies of such truncated SIC products can result in misleading statistics and favour data sets that systematically overestimate SIC. We describe a method to reconstruct the non-truncated distribution of SIC before the evaluation is performed. On the basis of this evaluation, we open a discussion about the overestimation of SIC in data products, with far-reaching consequences for surface heat flux estimations in winter. We also document inconsistencies in the behaviour of the weather filters used in products of group II, and we suggest advancing studies about the influence of these weather filters on SIA and SIE time series and their trends

Deep-ocean mixing driven by small-scale internal tides

Turbulent mixing in the ocean is key to regulate the transport of heat, freshwater and biogeochemical tracers, with strong implications for Earth’s climate. In the deep ocean, tides supply much of the mechanical energy required to sustain mixing via the generation of internal waves, known as internal tides, whose fate—the relative importance of their local versus remote breaking into turbulence—remains uncertain. Here, we combine a semi-analytical model of internal tide generation with satellite and in situ measurements to show that from an energetic viewpoint, small-scale internal tides, hitherto overlooked, account for the bulk (>50%) of global internal tide generation, breaking and mixing. Furthermore, we unveil the pronounced geographical variations of their energy proportion, ignored by current parameterisations of mixing in climate-scale models. Based on these results, we propose a physically consistent, observationally supported approach to accurately represent the dissipation of small-scale internal tides and their induced mixing in climate-scale models