An acreage response model for Arkansas rice farms

In recent years, market forces have signaled a strong demand for rice as well as other Arkansas crops. However, high fuel, fertilizer, and chemical costs have negatively impacted farm income, and these input costs are widely known to impact planting decisions of farmers. The goal of this study is to develop and estimate an acreage response model for rice. The model is used to compute acreage response elasticities and provides insight into roles that input costs and crop prices play in acreage decisions made by producers. Economic theory predicts that prices for important inputs such as fuels and fertilizers as well as the relative prices of rice and soybeans will impact acreage decisions. Soybean prices are expected to be important because most of the machinery needed to produce rice and soybeans is the same and these crops are already used commonly in rotation. Results of the study show that crop price variables do indeed play a significant role in producer planning. Short- and long-run own-price acreage response elasticities are estimated to be 0.69 and 1.19, respectively. Soybean prices have the expected negative impact on rice acreage with a cross-price elasticity of -0.33 in the short run and -0.57 in the long run. On the other hand, the expected economic impacts of input prices on rice acreage were not supported by the results. Estimated relationships were negative, as would be predicted by economic theory, but were not statistically significant

The Pathogenicity of Blue-Stain Fungi on Lodgepole Pines Attacked by Mountain Pine Beetle

In the western regions of North America, mountain pine beetle, Dendroctonus ponderosae Hopk., infestations take a tremendous toll of pines , especially lodgepole pine, Pinus contorta Dougl. var. latifolia Engelm.. Mass attack by the beetles is a devastating event for the trees. As well as girdling the tree, a massive inoculation of blue stain fungus complex (composed of several species of Ceratocystis, numerous yeasts and other mycelial fungi) is made beneath the bark. These fungi colonize and destroy the parenchyma tissue system of the host sapwood, primarily the ray parenchyma and resin duct epithelium. A blue stain is produced in the sapwood as a consequence of destruction of the sapwood parenchyma. The stain develops inward through the sapwood, and the transpiration stream is cut off. As more and more sapwood is stained, foliar water stress begins to increase. Foliage however, remains green and apparently healthy for up to 10 months after inoculation. When spring bud break begins the year following beetle attack, terminal buds of blue-stained trees begin to expand, then abort. Soon after, the needles of these trees fade to a reddish brown color. Transpiration stream disruption was not caused by penetration of tracheids by fungal hyphae; tyloses were not observed; nor was microconidial blockage of bordered pits seen. Though resin duct epithelium was eventually destroyed, little resin soaking was observed in the initial blue stained regions. Many bordered pits of tracheids in stained regions appeared to be aspirated, suggesting introduction of embolisms

Climate Change and Federal Crop Insurance

The federal crop insurance program is well-positioned today to promote resilient agricultural practices that mitigate the future impact of climate change. In light of climate change risk, this Article examines issues relating to climate change and the federal crop insurance program. Part I of this Article examines the present risk of climate change in agriculture and discusses recent steps taken to address climate change in agriculture in general, specifically within the federal crop insurance program. As a condition to federal crop insurance coverage, a farmer-insured must utilize “good farming practices” to obtain coverage for covered causes of loss. Part II examines the role of “good farming practices” determinations and its effects on climate change. This Article addresses three cases decided within the past five years and contends that the increasing number of cases in the federal courts indicate that an amendment to the “good farming practices” standard may have a significant effect in promoting climate change mitigation. This Article concludes by proposing an amendment to the “good farming practices” standard. The proposed standard dictates that if a farmer utilizes “sustainable, resilient and soil-building agricultural practices,” then such utilization must be weighed as a substantial factor in support of a “good farming practices” determination by the Risk Management Agency

What Do We Know about Young Volunteers? An Exploratory Study of Participation in Zooniverse

Citizen Science (CS) is an increasingly popular activity enacted either in the field or online. Volunteers participate in research activities such as data processing and analysis by, for example, identifying plants and animals. In this paper we examine young people’s participation in online CS projects hosted on the Zooniverse platform. This is an exploratory study, the first of its kind that focuses on young people, mainly 16–19 years old. It uses data analytics and visualisation techniques to capture participation in online CS, and in particular to answer the following questions: (a) What does young people’s participation look like in CS projects? (b) What Zooniverse projects do young people choose to participate in? and (3) What Zooniverse projects do young people choose together? Findings revealed five distinct engagement profiles characterising young people’s participation and identified certain projects as been more popular across participants. Implications for the design of online citizen science projects targeting young people are discussed

New Technologies Aid Understanding of the Factors Affecting Adélie Penguin Foraging

The Ross Sea (Figure 1) is home to 33% of the world’s Adélie penguins (Pygoscelis adeliae), as well as substantial numbers of Emperor penguins (Aptenodytes forsteri), Weddell seals (Leptonychotes weddellii), and pelagic birds (Smith et al., 2014). Among these, the Commission for the Conservation of Antarctic Marine Resources (CCAMLR) has designated the Adélie penguin an “indicator species” for monitoring ecosystem structure and function in the newly designated Ross Sea Region Marine Protected Area (RSR-MPA). This penguin, among the best-known seabirds, has been studied for decades at multiple locations with investigations that have delved into its population history (both recent and through thousands of years), survival strategies, responses to environmental changes, and feeding ecology (summarized in Ainley, 2002, with numerous papers published thereafter)

Sex-based differences in Adélie Penguin (Pygoscelis adeliae) chick growth rates and diet

Sexually size-dimorphic species must show some difference between the sexes in growth rate and/or length of growing period. Such differences in growth parameters can cause the sexes to be impacted by environmental variability in different ways, and understanding these differences allows a better understanding of patterns in productivity between individuals and populations. We investigated differences in growth rate and diet between male and female Adélie Penguin ( Pygoscelis adeliae ) chicks during two breeding seasons at Cape Crozier, Ross Island, Antarctica. Adélie Penguins are a slightly dimorphic species, with adult males averaging larger than adult females in mass (~11%) as well as bill (~8%) and flipper length (~3%). We measured mass and length of flipper, bill, tibiotarsus, and foot at 5-day intervals for 45 male and 40 female individually-marked chicks. Chick sex was molecularly determined from feathers. We used linear mixed effects models to estimate daily growth rate as a function of chick sex, while controlling for hatching order, brood size, year, and potential variation in breeding quality between pairs of parents. Accounting for season and hatching order, male chicks gained mass an average of 15.6 g d -1 faster than females. Similarly, growth in bill length was faster for males, and the calculated bill size difference at fledging was similar to that observed in adults. There was no evidence for sex-based differences in growth of other morphological features. Adélie diet at Ross Island is composed almost entirely of two species--one krill ( Euphausia crystallorophias ) and one fish ( Pleuragramma antarctica ), with fish having a higher caloric value. Using isotopic analyses of feather samples, we also determined that male chicks were fed a higher proportion of fish than female chicks. The related differences in provisioning and growth rates of male and female offspring provides a greater understanding of the ways in which ecological factors may impact the two sexes differently

Icebreaker dates and ice edge distance in McMurdo Sound, Antarctica from austral years 1956/1957 to 2014/2015 (McMurdo Predator Prey project)

Dataset: McMurdo Sound icebreaker dates and ice edge distanceThe icebreaker channel from the fast ice edge to McMurdo Station has been created each year since 1956, with the location of the channel remaining consistent, by and large, over the entire period. Dates of the icebreaker arrival at the fast ice edge and/or at McMurdo Station since 1957 were acquired from scientist and icebreaker logbooks and contractor records (DACSUSAP2012-13; pers. comm. P. McGillivary USCG), along with the distance, which was measured by radar from the fast ice edge to McMurdo Station on the date that the icebreaker began breaking fast ice. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/674992NSF Division of Polar Programs (NSF PLR) PLR-0944747, NSF Division of Polar Programs (NSF PLR) PLR-0944511, NSF Division of Polar Programs (NSF PLR) PLR-094469

Sea ice parameters near McMurdo Station, Antarctica from 1986 to 2013

Dataset: McMurdo Sound sea ice thicknessFast ice thickness and temperature data collected at the “sea ice runway” near McMurdo Station by the United States Antarctic Program (USAP) logistic support contractors and provided by the Ice Surveyor (J Scanniello). Fast ice measurements were taken at a suite of 16 stations along a 3000 m distance, and five stations across an orthogonal 1000 m distance. At each station, small holes were drilled through the fast ice and the thickness measured using a meter tape with a lever-arm that held the zero-point against the bottom of the fast ice. Thickness was measured for solid ice and did not include underlying platelet ice, nor overlying snow. Fast ice temperature was measured at 15 cm depth beneath the ice surface. Note that the sea ice runway area is routinely cleared of excess snow, which may affect the fast ice thickness and temperature measurements. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/675187NSF Division of Polar Programs (NSF PLR) PLR-0944747, NSF Division of Polar Programs (NSF PLR) PLR-0944511, NSF Division of Polar Programs (NSF PLR) PLR-094469

Chlorophyll data from McMurdo Sound, Antarctica from 2012 to 2015 (McMurdo Predator Prey project)

Dataset: McMurdo Sound chlorophyllDiscrete chlorophyll a data were collected as part of an ecosystem study in McMurdo Sound, which is located at the southern extent of the Ross Sea in the Southern Ocean. The major goal of this multi-disciplinary project was to assess the influence of top−down forcing (predation) on pelagic zooplankton and fish. Samples were collected using Niskin water bottles deployed through the fast ice (sea ice attached to land) during two spring/summer seasons: 3 November 2012 – 21 January 2013 and17 November 2014 – 1 January 2015. Water samples were collected at the surface and in the chlorophyll maximum, when present, as determined by a fluorescence sensor during a CTD cast. During 2012/2013, stations were located along a transect in the middle of McMurdo Sound, perpendicular to the fast ice edge. During 2014/2015, stations were located along the fast ice edge, and along three transects into the fast ice along the eastern side of the McMurdo Sound (Ross Island), in the middle of the Sound, and on the western side of the Sound. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/679685NSF Division of Polar Programs (NSF PLR) PLR-094451

Dates of sea ice movement and sea ice distance in McMurdo Sound, Antarctica from MODIS and SSMI imagery between 1978-2015 (McMurdo Predator Prey project)

Dataset: McMurdo Sound sea ice movement datesFast/sea ice movement was quantified from visible-wavelength images from the Moderate-resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites (250 m resolution; processing occurred for 2002/03-2014/15 seasons and Terra satellite date from 2000-2002 were not used) and sea ice concentration derived from the Scanning Multichannel Microwave Radiometer- and Special Sensor Microwave Imager-family passive microwave sensors (SSM/I; 25 km resolution; 1978/79-2014/15). MODIS data were acquired in one of two ways, from either processing of Level 1 swath data into “true color” images using SeaDAS software v. 6.4 (2002-2012), or from the Corrected Reflectance (True Color) layers of the NASA Worldview website (http://worldview.earthdata.nasa.gov/; 2012-2015). Fast ice areas were generated manually from clear-sky images by drawing polygons in GIS software; pack ice was excluded from analysis. The fast ice in MODIS images was sometimes obscured by clouds, so for days with missing imagery we interpolated linearly between valid data. From the MODIS imagery, we also measured the direct linear distance between McMurdo Station and the nearest open water. For SSM/I, daily or bi-daily fractional sea ice cover was extracted from data available at the National Snow and Ice Data Center (NSIDC). SSM/I ice concentration was retrieved from the NSDIC web site and ftp site (http://nsidc.org/data/seaice/). To minimize the biases inherent to the different data processing algorithms and in order to reduce the daily variability introduced by the movement of pack ice, we took the maximum of either the Bootstrap or NASATEAM processed values (Comiso, 2000; Cavalieri and others, 2015), and then used a 5-day median filter to smooth changes in sea ice concentration. To further compensate for short-term oscillations we masked ice concentrations greater than 80% when extracting the dates of changes in sea ice cover. For detecting the timing of sea ice changes, sea ice concentrations below 15% were excluded from our analysis, following the methods of Comiso and Steffen (2001).> To simplify discussion in the following, we use the inclusive term “fast/sea ice” to refer to fast ice as determined by MODIS and sea ice as determined by SSM/I. Fast/sea ice area was plotted over time, and the following sequential pattern of fast/sea ice events is identified: (1) initial fast/sea ice retreat from winter maximum; (2) final rapid fast/sea ice retreat to minimum extent; (3) fast/sea ice cover minimum in the entire McMurdo Sound; and (4) fast/sea ice advance. From the MODIS data, we additionally determined (5) fast ice cover minimum on the west side of the Sound; and (6) fast ice cover minimum on the east side of the Sound. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/674819NSF Division of Polar Programs (NSF PLR) PLR-0944747, NSF Division of Polar Programs (NSF PLR) PLR-0944511, NSF Division of Polar Programs (NSF PLR) PLR-094469