The Public Resource Management Game

Use of public resources for private economic gain is a longstanding, contested political issue. Public resources generate benefits beyond commodity uses, including recreation, environmental and ecological conservation and preservation, and existence and aesthetic values. We analyze this problem using a dynamic resource use game. Low use fees let commodity users capture more of the marginal benefit from private use. This increases the incentive to comply with government regulations. Optimal contracts therefore include public use fees that are lower than private rates. The optimal policy also includes random monitoring to prevent strategic learning and cheating on the use agreements and to avoid wasteful efforts to disguise noncompliant behavior. An optimal policy also includes a penalty for cheating beyond terminating the use contract. This penalty must be large enough that the commodity user who would gain the most from noncompliance experiences a negative expected net return.Renewable resources, public resources policy, optimal contracts

Comparing Performance of Methods to Deal with Differential Attrition in Lottery Based Evaluations

In randomized controlled trials, it is common for attrition rates to differ by lottery status, jeopardizing the identification of causal effects. Inverse probability weighting methods (Hirano et al, 2003; Busso et al., 2014) and estimation of informative bounds for the treatment effects (e.g. Lee, 2009; Angrist et al., 2006) have been used frequently to deal with differential attrition bias. This paper studies the performance of various methods by comparing the results using two datasets: a district-sourced dataset subject to considerable differential attrition, and an expanded state-sourced dataset with much less attrition, differential and overall. We compared the performance of different methods to correct for differential attrition in the district dataset, as well as we conducted simulation analyses to assess the sensitivity of bounding methods to their underlying assumptions. In our application, methods to correct differential attrition induced bias, whereas the unadjusted district level results were closer and more substantively similar to the estimated effects in the benchmark state dataset. Our simulation exercises showed that even small deviations from the underlying assumptions in bounding methods proposed by Angrist et al. (2006) increased bias in the estimates. In practice, researchers often do not have enough information to verify the extent to which these underlying assumptions are met, so we recommend using these methods with caution

Environmental Signatures for Habitability: What to Measure and How to Rank the Habitability Potential of Mars

The environmental signatures for habitability are not necessarily biosignatures, even though on Earth, they are definitive proof of habitability. It is the constant overprint of the chemical signatures of life that makes it difficult to recognize the chemical and physical properties of a potentially habitable environment as distinct from an inhabited one. Mars Science Laboratory (MSL) will soon embark on a mission to Mars to assess its past or present habitability, so it is useful to examine how we measure habitability on Earth and prepare for how that approach may differ for Mars. This exercise includes: (a) articulation of fundamental assumptions about habitability, (b) an inventory of factors that affect habitability, (c) development of metrics, measurement approach and implementation, and (d) a new classification scheme for planetary habitability that goes beyond the binary "yes" or "no." There may be dozens of factors that affect habitability and they can be weighted as a function of specific environment. However a robotic, in situ investigation even on Earth has constraints that prevent the measurement of every environmental factor, so metrics must be reduced to the most relevant subset, given available time, cost, technical feasibility and scientific importance. Many of the factors could be measured with a combination of orbital data and the MSL payload. We propose that, at a minimum, a designation of high habitability potential requires the following conditions be met: (a) thermally stable with respect to extremes and frequency of fluctuation, (b) has more than one energy source, (c) sufficient chemical diversity to make compounds with covalent and hydrogen bonding, (d) can moderate ionizing radiation enough to allow a stable or evolving pool of organic molecules, (e) must have water or other high quality polar solvent, (f) must be able to renew chemical resources (e.g., plate tectonics, volcanism or something else we haven't envisioned). A measurement approach we have taken to measure habitability on Earth is : 1. Study remote sensing data, maps, etc. 2. Decide how big an area to measure. 3. Determine the spatial sampling rate. 4. Determine the temporal sampling rate. 5. Determine the order of measurements 6. Decide where to begin measurements 7. Select locations at field site and proceed While science drives each of the steps, there are additional constraints, e.g., technical, time, cost, safety (risk). This approach is also executable on Mars. Measurement of past habitability is more challenging both for Earth and Mars where access to the past means subsurface access and confrontation with unknowns about preservation of the martian past. Some environments preserve evidence of past habitability better than others, and this is where selection of the landing site to maximize the preservation potential of habitability indicators will be key. Mars presents an opportunity to discover transitional states between habitable or not, and we offer a ranking scale for planetary habitability with Mars as the second test subject: CLASS ONE Uninhabitable and likely has never been so CLASS TWO Has a high potential but no confirmed observation of life (as defined above) CLASS THREE Inhabited (we find life) 3-A Globally inhabited 3-B Primitive life; early in its evolution, but not yet globally established 3-C Exists only in refugia -- planet heading toward class four CLASS FOUR Post-habitable (there once was life, but now it's gone) MSL provides an opportunity to carefully investigate the habitability of at least one site on Mars and it will reveal much about the possible states of planetary habitabilit

Do Financial Incentives Help Low-Performing Schools Attract and Keep Academically Talented Teachers? Evidence from California

This study capitalizes on a natural experiment that occurred in California between 2000 and 2002. In those years, the state offered a competitively allocated $20,000 incentive called the Governor's Teaching Fellowship (GTF) aimed at attracting academically talented, novice teachers to low-performing schools and retaining them in those schools for at least four years. Taking advantage of data on the career histories of 27,106 individuals who pursued California teaching licenses between 1998 and 2003, we use an instrumental variables strategy to estimate the unbiased impact of the GTF on the decisions of recipients to begin working in low-performing schools within two years after licensure program enrollment. We estimate that GTF recipients would have been less likely to teach in low-performing schools than observably similar counterparts had the GTF not existed, but that acquiring a GTF increased their probability of doing so by 28 percentage points. Examining retention patterns, we find that 75 percent of both GTF recipients and non-recipients who began working in low-performing schools remained in such schools for at least four years.

Effects of Dual-Language Immersion on Students’ Academic Performance

Using data from seven cohorts of language immersion lottery applicants in a large, urban school district, we estimate the causal effects of immersion on students’ test scores in reading, mathematics, and science, and on English learners’ (EL) reclassification. We estimate positive intent-to-treat (ITT) effects on reading performance in fifth and eighth grades, ranging from 13 to 22 percent of a standard deviation, reflecting 7 to 9 months of learning. We find little benefit in terms of mathematics and science performance, but also no detriment. By sixth and seventh grade, lottery winners’ probabilities of remaining classified as EL are three to four percentage points lower than those of their counterparts. This effect is stronger for ELs whose native language matches the partner language

Genome -Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is straindependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains forspecific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotyperelationships and to compare different organisms. To assist in the selection and development of strains with enhancedindustrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate,were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications

Using Student Achievement Data to Support Instructional Decision Making

As educators face increasing pressure from federal, state, and local accountability policies to improve student achievement, the use of data has become more central to how many educators evaluate their practices and monitor students’ academic progress (Knapp et al., 2006). Despite this trend, questions about how educators should use data to make instructional decisions remain mostly unanswered. In response, this guide provides a framework for using student achievement data to support instructional decision making. These decisions include, but are not limited to, how to adapt lessons or assignments in response to students’ needs, alter classroom goals or objectives, or modify student-grouping arrangements. The guide also provides recommendations for creating the organizational and technological conditions that foster effective data use. Each recommendation describes action steps for implementation, as well as suggestions for addressing obstacles that may impedeprogress. In adopting this framework, educators will be best served by implementing the recommendations in this guide together rather than individually

Geochemical, metagenomic and metaproteomic insights into trace metal utilization by methane-oxidizing microbial consortia in sulphidic marine sediments

Microbes have obligate requirements for trace metals in metalloenzymes that catalyse important biogeochemical reactions. In anoxic methane- and sulphide-rich environments, microbes may have unique adaptations for metal acquisition and utilization because of decreased bioavailability as a result of metal sulphide precipitation. However, micronutrient cycling is largely unexplored in cold (≤ 10°C) and sulphidic (> 1 mM ΣH_(2)S) deep-sea methane seep ecosystems. We investigated trace metal geochemistry and microbial metal utilization in methane seeps offshore Oregon and California, USA, and report dissolved concentrations of nickel (0.5–270 nM), cobalt (0.5–6 nM), molybdenum (10–5600 nM) and tungsten (0.3–8 nM) in Hydrate Ridge sediment porewaters. Despite low levels of cobalt and tungsten, metagenomic and metaproteomic data suggest that microbial consortia catalysing anaerobic oxidation of methane (AOM) utilize both scarce micronutrients in addition to nickel and molybdenum. Genetic machinery for cobalt-containing vitamin B_(12) biosynthesis was present in both anaerobic methanotrophic archaea (ANME) and sulphate-reducing bacteria. Proteins affiliated with the tungsten-containing form of formylmethanofuran dehydrogenase were expressed in ANME from two seep ecosystems, the first evidence for expression of a tungstoenzyme in psychrophilic microorganisms. Overall, our data suggest that AOM consortia use specialized biochemical strategies to overcome the challenges of metal availability in sulphidic environments