The fragility of meta-regression models in observational research

Many meta-regression analyses that synthesize estimates from primary studies have now been published in economics. Meta-regression models attempt to infer the presence of genuine empirical effects even if the authors of primary studies select statistically significant and theory-confirming estimates for publication. Meta-regression models were originally developed for the synthesis of experimental research where randomization ensures unbiased and consistent estimation of the effect of interest. Most economics research is, however, observational and authors of primary studies can search across different regression specifications for statistically significant and theory-confirming estimates. Each regression specification may possibly suffer from biases such as omitted-variable biases that result in biased and inconsistent estimation of the effect of interest. We show that if the authors of primary studies search for statistically significant and theory-confirming estimates, meta-regression models tend to systematically make false-positive findings of genuine empirical effects. The ubiquity of such search processes for specific results may limit the applicability of meta-regression models in identifying genuine empirical effects in economics

Scale Model of a Soil Aggregate and Associated Organisms: A Teaching Tool for Soil Ecology

Soil is a complex habitat for diverse biota. A significant challenge in teaching soil ecology is our inability to observe organisms as they live and interact in the soil. The objective of this article is to describe an interactive class project to help students visualize the sizes of different groups of soil organisms and to relate these to soil structural components. This project was carried out by students in an upper-level undergraduate soil ecology class. It involved the design and construction of a 4000× scale model of a soil aggregate and its associated organisms. The body of the model was made from inexpensive, lightweight materials and had a diameter of approximately 1 m to depict a 0.25-mm aggregate. Students identified and discussed appropriate size ranges and construction materials for the model’s bacteria, fungi, nematodes, mites, springtails, and other components. Instructor-guided questions addressed size and arrangement of sand, silt, and clay particles; pores; and organic matter in a typical soil aggregate. The model is a useful tool for conveying physical and ecological relationships among soil organisms and is adaptable for use at diverse educational levels

Can declining energy intensity mitigate climate change? Decomposition and meta-regression results

Drawing on the Kaya identity, we assess the role of the main driver of the decline in carbon intensity, namely the (economic) energy intensity. Using meta-significance testing for a sample of 44 studies, dealing with the causality between energy and GDP, we find that both variables are strongly coupled. Hence, after having exhausted energy savings from nonrecurring structural changes, the economic energy intensity may soon converge than being arbitrarily reducible. We suggest, therefore, not to rely on further reductions of economic energy intensity but rather to invest in the reduction of the carbon intensity of energy to mitigate climate change

Gauge invariance in two-particle scattering

It is shown how gauge invariance is obtained for the coupling of a photon to a two-body state described by the solution of the Bethe-Salpeter equation. This is illustrated both for a complex scalar field theory and for interaction kernels derived from chiral effective Lagrangians.Comment: 16 pages, 2 figures, references added and commented o

Identifying genuine effects in observational research by means of meta-regressions

Meta-regression models are increasingly utilized to integrate empirical results across studies while controlling for the potential threats of data-mining and publication bias. We propose extended meta-regression models and evaluate their performance in identifying genuine empirical effects by means of a comprehensive simulation study for various scenarios that are prevalent in empirical economics. We can show that the meta-regression models here proposed systematically outperform the prior gold standard of meta-regression analysis of regression coefficients. Most meta-regression models are robust to the presence of publication bias, but data-mining bias leads to seriously inflated type I errors and has to be addressed explicitly

Post-training load-related changes of auditory working memory: An EEG study

Working memory (WM) refers to the temporary retention and manipulation of information, and its capacity is highly susceptible to training. Yet, the neural mechanisms that allow for increased performance under demanding conditions are not fully understood. We expected that post-training efficiency in WM performance modulates neural processing during high load tasks. We tested this hypothesis, using electroencephalography (EEG) (N = 39), by comparing source space spectral power of healthy adults performing low and high load auditory WM tasks. Prior to the assessment, participants either underwent a modality-specific auditory WM training, or a modality-irrelevant tactile WM training, or were not trained (active control). After a modality-specific training participants showed higher behavioral performance, compared to the control. EEG data analysis revealed general effects of WM load, across all training groups, in the theta-, alpha-, and beta-frequency bands. With increased load theta-band power increased over frontal, and decreased over parietal areas. Centro-parietal alpha-band power and central beta-band power decreased with load. Interestingly, in the high load condition a tendency toward reduced beta-band power in the right medial temporal lobe was observed in the modality-specific WM training group compared to the modality-irrelevant and active control groups. Our finding that WM processing during the high load condition changed after modality-specific WM training, showing reduced beta-band activity in voice-selective regions, possibly indicates a more efficient maintenance of task-relevant stimuli. The general load effects suggest that WM performance at high load demands involves complementary mechanisms, combining a strengthening of task-relevant and a suppression of task-irrelevant processing

Governance for integrated water resources management in a river-basin context: proceedings of a regional seminar, Bangkok, May, 2002

Water resource management / River basins / Governance / Institutional development / Groundwater irrigation / Water policy / Water allocation / Water demand / Irrigation efficiency / Models / Case studies

Equity-Efficiency Optimizing Resource Allocation: The Role of Time Preferences in a Repeated Irrigation Game

We study repeated water allocation decisions among small scale irrigation users in Tanzania. In a treatment replicating water scarcity conditions, convexities in production make that substantial efficiency gains can be obtained by deviating from equal sharing, leading to an equity–efficiency trade-off. In a repeated game setting, it becomes possible to reconcile efficiency with equity by rotating the person who receives the largest share, but such a strategy requires a longer run perspective. Correlating experimental data from an irrigation game with individual time preference data, we find that less patient irrigators are less likely to use a rotation strategy

Fungi isolated from Miscanthus and sugarcane: biomass conversion, fungal enzymes, and hydrolysis of plant cell wall polymers.

BackgroundBiofuel use is one of many means of addressing global change caused by anthropogenic release of fossil fuel carbon dioxide into Earth's atmosphere. To make a meaningful reduction in fossil fuel use, bioethanol must be produced from the entire plant rather than only its starch or sugars. Enzymes produced by fungi constitute a significant percentage of the cost of bioethanol production from non-starch (i.e., lignocellulosic) components of energy crops and agricultural residues. We, and others, have reasoned that fungi that naturally deconstruct plant walls may provide the best enzymes for bioconversion of energy crops.ResultsPreviously, we have reported on the isolation of 106 fungi from decaying leaves of Miscanthus and sugarcane (Appl Environ Microbiol 77:5490-504, 2011). Here, we thoroughly analyze 30 of these fungi including those most often found on decaying leaves and stems of these plants, as well as four fungi chosen because they are well-studied for their plant cell wall deconstructing enzymes, for wood decay, or for genetic regulation of plant cell wall deconstruction. We extend our analysis to assess not only their ability over an 8-week period to bioconvert Miscanthus cell walls but also their ability to secrete total protein, to secrete enzymes with the activities of xylanases, exocellulases, endocellulases, and beta-glucosidases, and to remove specific parts of Miscanthus cell walls, that is, glucan, xylan, arabinan, and lignin.ConclusionThis study of fungi that bioconvert energy crops is significant because 30 fungi were studied, because the fungi were isolated from decaying energy grasses, because enzyme activity and removal of plant cell wall components were recorded in addition to biomass conversion, and because the study period was 2 months. Each of these factors make our study the most thorough to date, and we discovered fungi that are significantly superior on all counts to the most widely used, industrial bioconversion fungus, Trichoderma reesei. Many of the best fungi that we found are in taxonomic groups that have not been exploited for industrial bioconversion and the cultures are available from the Centraalbureau voor Schimmelcultures in Utrecht, Netherlands, for all to use