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This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.
The AlpArray seismic network
(2018)
The AlpArray programme is a multinational, European consortium to advance our understanding of orogenesis and its relationship to mantle dynamics, plate reorganizations, surface processes and seismic hazard in the Alps-Apennines-Carpathians-Dinarides orogenic system. The AlpArray Seismic Network has been deployed with contributions from 36 institutions from 11 countries to map physical properties of the lithosphere and asthenosphere in 3D and thus to obtain new, high-resolution geophysical images of structures from the surface down to the base of the mantle transition zone. With over 600 broadband stations operated for 2 years, this seismic experiment is one of the largest simultaneously operated seismological networks in the academic domain, employing hexagonal coverage with station spacing at less than 52 km. This dense and regularly spaced experiment is made possible by the coordinated coeval deployment of temporary stations from numerous national pools, including ocean-bottom seismometers, which were funded by different national agencies. They combine with permanent networks, which also required the cooperation of many different operators. Together these stations ultimately fill coverage gaps. Following a short overview of previous large-scale seismological experiments in the Alpine region, we here present the goals, construction, deployment, characteristics and data management of the AlpArray Seismic Network, which will provide data that is expected to be unprecedented in quality to image the complex Alpine mountains at depth.
Sustainable land use in Mountain Regions under global change synthesis across scales and disciplines
(2013)
Mountain regions provide essential ecosystem goods and services (EGS) for both mountain dwellers and people living outside these areas. Global change endangers the capacity of mountain ecosystems to provide key services. The Mountland project focused on three case study regions in the Swiss Alps and aimed to propose land-use practices and alternative policy solutions to ensure the provision of key EGS under climate and land-use changes. We summarized and synthesized the results of the project and provide insights into the ecological, socioeconomic, and political processes relevant for analyzing global change impacts on a European mountain region. In Mountland, an integrative approach was applied, combining methods from economics and the political and natural sciences to analyze ecosystem functioning from a holistic human-environment system perspective. In general, surveys, experiments, and model results revealed that climate and socioeconomic changes are likely to increase the vulnerability of the EGS analyzed. We regard the following key characteristics of coupled human-environment systems as central to our case study areas in mountain regions: thresholds, heterogeneity, trade-offs, and feedback. Our results suggest that the institutional framework should be strengthened in a way that better addresses these characteristics, allowing for (1) more integrative approaches, (2) a more network-oriented management and steering of political processes that integrate local stakeholders, and (3) enhanced capacity building to decrease the identified vulnerability as central elements in the policy process. Further, to maintain and support the future provision of EGS in mountain regions, policy making should also focus on project-oriented, cross-sectoral policies and spatial planning as a coordination instrument for land use in general.
We investigated the influence of teacher feedback on the social acceptance of peers with intellectual disabilities and peers without disabilities. A computer task was administered to 601 students in grades 3 and 4. Twenty-six per cent of the students attend an inclusive school; the others are in regular schools without students with special educational needs. Participants are introduced to ‘new’ virtual classmates, one student with Down syndrome (DS), and one control student with no obvious disability. Additionally, teacher feedback and feedback about fun playing with the new classmates is given. Social acceptance is evaluated by asking if one would like to sit next to him/her. Both feedbacks showed a strong effect. The child with DS was less socially accepted than the child without disability. No difference regarding the social acceptance of the students with DS was found between students from inclusive and regular classes. Students from regular classes rate the social acceptance of the student without disabilities significantly higher than students from inclusive classrooms.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Hydrological response to earthquakes has long been observed, yet the mechanisms responsible still remain unclear and likely vary in space and time. This study explores the base flow response in small upland catchments of the Coastal Range of south-central Chile after the M-W 8.8 Maule earthquake of 27 February 2010. An initial decline in streamflow followed by an increase of up to 400% of the discharge measured immediately before the earthquake occurred, and diurnal streamflow oscillations intensified after the earthquake. Neither response time, nor time to maximum streamflow discharge showed any relationship with catchment topography or size, suggesting non-uniform release of water across the catchments. The fast response, unaffected stream water temperatures and a simple diffusion model point to the sandy saprolite as the source of the excess water. Base flow recession analysis reveals no evidence for substantial enhancement of lateral hydraulic conductivity in the saprolite after the earthquake. Seismic energy density reached similar to 170 J/m(3) for the main shock and similar to 0.9 J/m(3) for the aftershock, exceeding the threshold for liquefaction by undrained consolidation only during the main shock. Although increased hydraulic gradient due to ground acceleration-triggered, undrained consolidation is consistent with empirical magnitude-distance relationships for liquefaction, the lack of independent evidence for liquefaction means that enhanced vertical permeability (probably in combination with co-seismic near-surface dilatancy) cannot be excluded as a potential mechanism. Undrained consolidation may have released additional water from the saturated saprolite into the overlying soil, temporarily reducing water transfer to the creeks but enlarging the cross-section of the saturated zone, which in turn enhanced streamflow after establishment of a new hydraulic equilibrium. The enlarged saturated zone facilitated water uptake by roots and intensified evapotranspiration.
Timber harvesting by clear cutting is known to impose environmental impacts, including severe disturbance of the soil hydraulic properties which intensify the frequency and magnitude of surface runoff and soil erosion. However, it remains unanswered if harvest areas act as sources or sinks for runoff and soil erosion and whether such behavior operates in a steady state or evolves through time. For this purpose, 92 small-scale rainfall simulations of different intensities were carried out under pine plantation conditions and on two clear-cut harvest areas of different age. Nonparametrical Random Forest statistical models were set up to quantify the impact of environmental variables on the hydrological and erosion response. Regardless of the applied rainfall intensity, runoff always initiated first and yielded most under plantation cover. Counter to expectations, infiltration rates increased after logging activities. Once a threshold rainfall intensity of 20mm/h was exceeded, the younger harvest area started to act as a source for both runoff and erosion after connectivity was established, whereas it remained a sink under lower applied rainfall intensities. The results suggest that the impact of microtopography on surface runoff connectivity and water-repellent properties of the topsoil act as first-order controls for the hydrological and erosion processes in such environments. Fast rainfall-runoff response, sediment-discharge-hystereses, and enhanced postlogging groundwater recharge at catchment scale support our interpretation. At the end, we show the need to account for nonstationary hydrological and erosional behavior of harvest areas, a fact previously unappreciated in predictive models.