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We present observations from two field deployments of a calibrated tiltmeter that we name the Self‐Calibrating Tilt Accelerometer (SCTA). The tiltmeter is based upon a triaxial quartz crystal accelerometer; the horizontal channels measure tilt and are periodically rotated into the vertical to obtain a measurement of the acceleration of gravity. Changes in the measured total acceleration are ascribed to drift in the vertical channel and used as calibrations for removing that same drift from the tilt time series observed between calibrations. Changes in the span (sensitivity) of the accelerometer channels can also be measured by calibrating them pointing up and down. A 3‐year test on the seafloor at Axial Seamount show that the calibrations are consistent with a linear‐exponential model of drift to a RMS residual of ∼0.5 μg (μrad). The calibrated tilt time series was impacted by platform settling for the first 2 years, but after repositioning the tiltmeter, the calibrated observations were consistent for the final year with the tilt observed on a nearby LILY tiltmeter, within an assumed level of drift for the unconstrained LILY sensor. A separate 15‐month test in a stable vault at Piñon Flat Observatory was complicated by seasonal temperature variations of >5°C; the calibrations are consistent with a linear‐exponential model of drift to ∼2 μg RMS when temperature and temperature time‐derivative dependence is included. Similarly, the calibrated tilt time series was impacted by thermal deformation of the SCTA assembly. A future test in a thermally and tectonically stable borehole will be required to assess the accuracy of the SCTA. Plain Language Summary: We developed a new instrument for measuring the tilt of a surface to a high degree of accuracy, on the order of a millionth of a radian. This instrument, the Self‐Calibrating Tilt Accelerometer (SCTA), combines three sensor channels that measure acceleration, arranged so that two channels are horizontal at right angles and the other is vertical. Tilting of the ground surface moves the horizontal channels toward alignment with the (vertical) gravitational acceleration, producing an observable signal. The SCTA can rotate to put any of the three channels into the vertical, where they can be calibrated against the full, effectively constant gravitational acceleration. These calibrations correct the horizontal tilt measurements for artificial signals generated within the sensors, yielding reliable measurements of the tilt of the ground surface. We present data from two deployments of the SCTA concept, one land‐based at Piñon Flats Observatory and the other seafloor‐based at Axial Seamount. At Axial, there is ongoing tilting of the seafloor from volcanic inflation that the SCTA measures consistent with a nearby, independent sensor. Piñon Flats should be tectonically stable, but seasonal temperature fluctuations at the site induced apparent tilt signals from internal deformation of the SCTA assembly. Key Points: A 3‐axis quartz crystal accelerometer is calibrated against gravity to remove drift from measurements of tilt in the horizontal channelsCalibrations for separate field tests in a vault and on the seafloor are fit by a linear‐exponential drift model to ∼1 μg residualCalibrations suggest variable span changes by sensor, from approximately 1–5 μg/yr, or 1%–22% of the respective drift rate [ABSTRACT FROM AUTHOR]

Regulation of Energy Markets: Economic Mechanisms and Policy Evaluation, by Machiel Mulder (Springer International Publishing, 2021), 361 pages, ISBN: 978-3-030-58318-7 (hardback), ISBN 978-3-030-58319-4 (ebook). This timely and highly readable textbook [...]

This paper offers an accessible discussion of graphical causal models and how such a framework can be used to help identify causal relations. A graphical causal model represents a researcher's qualitative assumptions. As a result of the credibility revolution, there is growing interest to properly estimate cause-and-effect relationships. Using several examples, we illustrate how graphical models can and cannot be used to identify causation from observational data. Further, we offer a replication of a previous study that explored college enrolment by high school seniors who were eligible for student aid. From the original study, we use a graphical causal model to motivate the quantitative and qualitative modelling assumptions. Using a similar difference-in-difference approach based on propensity score matching, we estimate a smaller average treatment effect than the original study. The smaller estimated effect arguably stems from the graphical causal model's delineation of the original model specification. [ABSTRACT FROM AUTHOR]

Lead poisoning is a primary factor impeding the survival and recovery of the critically endangered California Condor (Gymnogyps californianus). However, the frequency and magnitude of lead exposure in condors is not well-known in part because most blood lead monitoring occurs biannually, and biannual blood samples capture only approximately 10% of a bird's annual exposure history. We investigated the use of growing feathers from free-flying condors in California to establish a bird's lead exposure history. We show that lead concentration and stable lead isotopic composition analyses of sequential feather sections and concurrently collected blood samples provided a comprehensive history of lead exposure over the 2-4 month period of feather growth. Feather analyses identified exposure events not evident from blood monitoring efforts, and by fitting an empirically derived timeline to actively growing feathers, we were able to estimate the time frame for specific lead exposure events. Our results demonstrate the utility of using sequentially sampled feathers to reconstruct lead exposure history. Since exposure risk in individuals is one determinant of population health, our findings should increase the understanding of population-level effects from lead poisoning in condors; this information may also be helpful for other avian species potentially impacted by lead poisoning.

While markets for agricultural commodities are often global, markets for cropland can be highly localized. Soil makeup and climate also tend to make farmland rental markets localized. This study compares several econometric models to measure the extent of spatial spillovers within these markets. A fully dynamic spatial model estimated on cropland transactions shows that sales are highly localized in the short term but face greater neighboring spillovers in the long term. Accounting for longer-term spatial interdependence of farmland markets can help to improve land value forecasts. [ABSTRACT FROM AUTHOR]