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USGS2026

Fifteen years of WRTDS for advancing water-quality science: A critical review of methodological developments and global applications

Contamination by nutrients, major ions, and metals poses a major threat to global water sustainability. Understanding how these pollutants vary across time and space requires long-term monitoring and robust statistical approaches. Traditional methods, however, often struggle to account for streamflow variability, seasonality, and nonlinear responses. Introduced in 2010, the Weighted Regressions on Time, Discharge, and Season (WRTDS) method offers a flexible, data-driven framework that generates both observed and flow-normalized estimates of concentration and load. Over the past 15 years, WRTDS has become a state-of-the-art tool for water-quality science and management, with applications spanning a wide range of hydrologic, climatic, and policy contexts─including major watersheds across North America, Europe, Asia, Australia, and the Arctic. In this review of WRTDS, we document the method’s major advancements, examine its expanding geographic and thematic applications, and summarize its relevance to water-quality management programs and policies worldwide. We also discuss its performance relative to other regression and machine-learning approaches. Finally, we identify key priorities for future development to support the continued evolution of WRTDS as a trusted and practical tool for scientists and managers working to protect and sustain water resources.

Environmental Science and Technology↗

USGS2012

Perils of correlating CUSUM-transformed variables to infer ecological relationships (Breton et al. 2006; Glibert 2010)

We comment on a nonstandard statistical treatment of time-series data first published by Breton et al. (2006) in Limnology and Oceanography and, more recently, used by Glibert (2010) in Reviews in Fisheries Science. In both papers, the authors make strong inferences about the underlying causes of population variability based on correlations between cumulative sum (CUSUM) transformations of organism abundances and environmental variables. Breton et al. (2006) reported correlations between CUSUM-transformed values of diatom biomass in Belgian coastal waters and the North Atlantic Oscillation, and between meteorological and hydrological variables. Each correlation of CUSUM-transformed variables was judged to be statistically significant. On the basis of these correlations, Breton et al. (2006) developed "the first evidence of synergy between climate and human-induced river-based nitrate inputs with respect to their effects on the magnitude of spring Phaeocystis colony blooms and their dominance over diatoms."

Limnology and Oceanography↗

USGS2025

Missing data in ecology: Syntheses, clarifications, and considerations

In ecology and related sciences, missing data are common and occur in a variety of different contexts. When missing data are not handled properly, subsequent statistical estimates tend to be biased, inefficient, and lack proper confidence interval coverage. Missing data are often grouped into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). We review each category and compare their benefits and drawbacks. We review several approaches to handling missing data including complete case analysis, imputation, inverse probability weighting, and data augmentation. We clarify what types of variables should accompany imputation methods and how those variables are influenced by the analysis methods. Additionally, we discuss missing data that lack a formal basis for measurement and hence are fundamentally different from MCAR, MAR, and MNAR missing data. Throughout, we introduce concepts and numeric examples using both simulated data and data from the United States Environmental Protection Agency's 2016 National Wetland Condition Assessment. We conclude by providing five considerations for ecologists and other scientists handling missing data.

Ecological Monographs↗

USGS2001

Statistical self-similarity of width function maxima with implications to floods

Recently a new theory of random self-similar river networks, called the RSN model, was introduced to explain empirical observations regarding the scaling properties of distributions of various topologic and geometric variables in natural basins. The RSN model predicts that such variables exhibit statistical simple scaling, when indexed by Horton-Strahler order. The average side tributary structure of RSN networks also exhibits Tokunaga-type self-similarity which is widely observed in nature. We examine the scaling structure of distributions of the maximum of the width function for RSNs for nested, complete Strahler basins by performing ensemble simulations. The maximum of the width function exhibits distributional simple scaling, when indexed by Horton-Strahler order, for both RSNs and natural river networks extracted from digital elevation models (DEMs). We also test a powerlaw relationship between Horton ratios for the maximum of the width function and drainage areas. These results represent first steps in formulating a comprehensive physical statistical theory of floods at multiple space-time scales for RSNs as discrete hierarchical branching structures. ?? 2001 Published by Elsevier Science Ltd.

Advances in Water Resources↗

USGS2011

Landsat 8 on-orbit characterization and calibration system

The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.

Conference Paper↗

USGS1991

40Ar/39Ar age of Cretaceous-Tertiary boundary tektites from Haiti

40 Ar/ 39 Ar dating of tektites discovered recently in Cretaceous-Tertiary (K-T) boundary marine sedimentary rocks on Haiti indicates that the K-T boundary and impact event are coeval at 64.5 ± 0.1 million years ago. Sanidine from a bentonite that lies directly above the K-T boundary in continental, coal-bearing, sedimentary rocks of Montana was also dated and has a 40 Ar/ 39 Ar age of 64.6 ± 0.2 million years ago, which is indistinguishable statistically from the age of the tektites.

Science↗

USGS2021

Statistical methods used in research concerning endangered and threatened animal species of Puerto Rico: A meta-study

A concern about statistics in wildlife studies, particularly of endangered and threatened species, is whether the data collected meet the assumptions necessary for the use of parametric statistics. This study identified published papers on the nine endangered and six threatened species found only on Puerto Rico using five different databases. The results from the Zoological Record database identified the most articles, including all identified by the other databases. Of the 222 identified articles, 108 included some form of statistics, 26 used only descriptive statistics, 34 included only parametric statistics, 26 used only nonparametric statistics, and 22 reported both parametric and nonparametric statistical analyses. This meta-study showed that the percentage of articles with no statistical treatment decreased in the most recent 20 years, and that although parametric statistics continue to be the most commonly used in published wildlife studies of Puerto Rican wildlife, there has been a distinct increase in the use of nonparametric statistics over time.

Caribbean Journal of Science↗

USGS2016

Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias

Biological monitoring programmes are increasingly relying upon large volumes of citizen-science data to improve the scope and spatial coverage of information, challenging the scientific community to develop design and model-based approaches to improve inference. Recent statistical models in ecology have been developed to accommodate false-negative errors, although current work points to false-positive errors as equally important sources of bias. This is of particular concern for the success of any monitoring programme given that rates as small as 3% could lead to the overestimation of the occurrence of rare events by as much as 50%, and even small false-positive rates can severely bias estimates of occurrence dynamics. We present an integrated, computationally efficient Bayesian hierarchical model to correct for false-positive and false-negative errors in detection/non-detection data. Our model combines independent, auxiliary data sources with field observations to improve the estimation of false-positive rates, when a subset of field observations cannot be validated a posteriori or assumed as perfect. We evaluated the performance of the model across a range of occurrence rates, false-positive and false-negative errors, and quantity of auxiliary data. The model performed well under all simulated scenarios, and we were able to identify critical auxiliary data characteristics which resulted in improved inference. We applied our false-positive model to a large-scale, citizen-science monitoring programme for anurans in the north-eastern United States, using auxiliary data from an experiment designed to estimate false-positive error rates. Not correcting for false-positive rates resulted in biased estimates of occupancy in 4 of the 10 anuran species we analysed, leading to an overestimation of the average number of occupied survey routes by as much as 70%. The framework we present for data collection and analysis is able to efficiently provide reliable inference for occurrence patterns using data from a citizen-science monitoring programme. However, our approach is applicable to data generated by any type of research and monitoring programme, independent of skill level or scale, when effort is placed on obtaining auxiliary information on false-positive rates.

Methods in Ecology and Evolution↗

USGS2024

An integrative paradigm for building causal knowledge

A core aspiration of the ecological sciences is to determine how systems work, which implies the challenge of developing a causal understanding. Causal inference has long been approached from a statistical perspective, which can be limited and restrictive for a variety of reasons. Ecologists and other natural scientists have historically pursued mechanistic knowledge as an alternative approach to causal understanding, though without explicit reference to the requirements of causal statistics. In this paper, I describe the premises of an expanded paradigm for causal studies, the Integrative Causal Investigation Paradigm, that subsumes causal statistics and mechanistic investigation into a multi-evidence approach. This paradigm is distinct from the one articulated by causal statistics in that it (1) focuses its attention on the long-term goal of building causal knowledge across multiple studies and (2) recognizes the essential role of mechanistic investigations in establishing a causal understanding. The Integrative Paradigm, consequentially, proposes that there are multiple methodological routes to building causal knowledge and thus represents a pluralistic perspective. This paper begins by describing the crux of the problem faced by causal statistics. To understand this problem, it should be recognized that the word causal has multiple meanings and a variety of evidential standards. An expanded vocabulary is developed so as to reduce ambiguities and clarify critical issues. I further show by example that there is an important ingredient typically omitted from consideration in causal statistics, which is the known information related to the mechanisms underlying relationships being evaluated. To address this issue, I describe a procedure, Causal Knowledge Analysis, that involves an evaluation and compilation of existing evidence indicative of causal content and the features of mechanisms. Causal Knowledge Analysis is applied to three example situations to illustrate the process and its potential for contributing to the development of causal knowledge. The implications of adopting the proposed paradigm and associated procedures are discussed and include the potential for advancing ecology, the potential for clarifying causal methodology, and the potential for contributing to predictive forecasting.

Ecological Monographs↗

USGS2016

Structure of high latitude currents in global magnetospheric-ionospheric models

Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.

Space Science Reviews↗

USGS2009

Effects of winter atmospheric circulation on temporal and spatial variability in annual streamflow in the western United States

Winter mean 700-hectoPascal (hPa) height anomalies, representing the average atmospheric circulation during the snow season, are compared with annual streamflow measured at 140 streamgauges in the western United States. Correlation and anomaly pattern analyses are used to identify relationships between winter mean atmospheric circulation and temporal and spatial variability in annual streamflow. Results indicate that variability in winter mean 700-Hpa height anomalies accounts for a statistically significant portion of the temporal variability in annual streamflow in the western United States. In general, above-average annual streamflow is associated with negative winter mean 700-Hpa height anomalies over the eastern North Pacific Ocean and/or the western United States. The anomalies produce an anomalous flow of moist air from the eastern North Pacific Ocean into the western United States that increases winter precipitation and snowpack accumulations, and subsequently streamflow. Winter mean 700-hPa height anomalies also account for statistically significant differences in spatial distributions of annual streamflow. As part of this study, winter mean atmospheric circulation patterns for the 40 years analysed were classified into five winter mean 700-hPa height anomaly patterns. These patterns are related to statistically significant and physically meaningful differences in spatial distributions of annual streamflow.

Hydrological Sciences Journal↗

USGS2011

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models.

Maine↗

USGS2001

Suggestions for presenting the results of data analyses

We give suggestions for the presentation of research results from frequentist, information-theoretic, and Bayesian analysis paradigms, followed by several general suggestions. The information-theoretic and Bayesian methods offer alternative approaches to data analysis and inference compared to traditionally used methods. Guidance is lacking on the presentation of results under these alternative procedures and on nontesting aspects of classical frequentists methods of statistical analysis. Null hypothesis testing has come under intense criticism. We recommend less reporting of the results of statistical tests of null hypotheses in cases where the null is surely false anyway, or where the null hypothesis is of little interest to science or management.

Journal of Wildlife Management↗

USGS2007

Earthquake likelihood model testing

INTRODUCTION The Regional Earthquake Likelihood Models (RELM) project aims to produce and evaluate alternate models of earthquake potential (probability per unit volume, magnitude, and time) for California. Based on differing assumptions, these models are produced to test the validity of their assumptions and to explore which models should be incorporated in seismic hazard and risk evaluation. Tests based on physical and geological criteria are useful but we focus on statistical methods using future earthquake catalog data only. We envision two evaluations: a test of consistency with observed data and a comparison of all pairs of models for relative consistency. Both tests are based on the likelihood method, and both are fully prospective ( i.e. , the models are not adjusted to fit the test data). To be tested, each model must assign a probability to any possible event within a specified region of space, time, and magnitude. For our tests the models must use a common format: earthquake rates in specified “bins” with location, magnitude, time, and focal mechanism limits. Seismology cannot yet deterministically predict individual earthquakes; however, it should seek the best possible models for forecasting earthquake occurrence. This paper describes the statistical rules of an experiment to examine and test earthquake forecasts. The primary purposes of the tests described below are to evaluate physical models for earthquakes, assure that source models used in seismic hazard and risk studies are consistent with earthquake data, and provide quantitative measures by which models can be assigned weights in a consensus model or be judged as suitable for particular regions. In this paper we develop a statistical method for testing earthquake likelihood models. A companion paper ( Schorlemmer and Gerstenberger 2007 , this issue) discusses the actual implementation of these tests in the framework of the RELM initiative. Statistical testing of hypotheses is a common task and a wide range of possible testing procedures exist. Jolliffe and Stephenson ( 2003 ) present different forecast verifications from atmospheric science, among them likelihood testing of probability forecasts and testing the occurrence of binary events. Testing binary events requires that for each forecasted event, the spatial, temporal and magnitude limits be given. Although major earthquakes can be considered binary events, the models within the RELM project express their forecasts on a spatial grid and in 0.1 magnitude units; thus the results are a distribution of rates over space and magnitude. These forecasts can be tested with likelihood tests. In general, likelihood tests assume a valid null hypothesis against which a given hypothesis is tested. The outcome is either a rejection of the null hypothesis in favor of the test hypothesis or a nonrejection, meaning the test hypothesis cannot outperform the null hypothesis at a given significance level. Within RELM, there is no accepted null hypothesis and thus the likelihood test needs to be expanded to allow comparable testing of equipollent hypotheses. To test models against one another, we require that forecasts are expressed in a standard format: the average rate of earthquake occurrence within pre-specified limits of hypocentral latitude, longitude, depth, magnitude, time period, and focal mechanisms. Focal mechanisms should either be described as the inclination of P -axis, declination of P -axis, and inclination of the T -axis, or as strike, dip, and rake angles. Schorlemmer and Gerstenberger ( 2007 , this issue) designed classes of these parameters such that similar models will be tested against each other. These classes make the forecasts comparable between models. Additionally, we are limited to testing only what is precisely defined and consistently reported in earthquake catalogs. Therefore it is currently not possible to test such information as fault rupture length or area, asperity location, etc. Also, to account for data quality issues, we allow for location and magnitude uncertainties as well as the probability that an event is dependent on another event. As we mentioned above, only models with comparable forecasts can be tested against each other. Our current tests are designed to examine grid-based models. This requires that any fault-based model be adapted to a grid before testing is possible. While this is a limitation of the testing, it is an inherent difficulty in any such comparative testing. Please refer to appendix B for a statistical evaluation of the application of the Poisson hypothesis to fault-based models. The testing suite we present consists of three different tests: L-Test, N-Test, and R-Test. These tests are defined similarily to Kagan and Jackson ( 1995 ). The first two tests examine the consistency of the hypotheses with the observations while the last test compares the spatial performances of the models.

Seismological Research Letters↗

USGS2018

Kinematics of the 2015 San Ramon, California earthquake swarm: Implications for fault zone structure and driving mechanisms

Earthquake swarms represent a sudden increase in seismicity that may indicate a heterogeneous fault-zone, the involvement of crustal fluids and/or slow fault slip. Swarms sometimes precede major earthquake ruptures. An earthquake swarm occurred in October 2015 near San Ramon, California in an extensional right step-over region between the northern Calaveras Fault and the Concord–Mt. Diablo fault zone, which has hosted ten major swarms since 1970. The 2015 San Ramon swarm is examined here from 11 October through 18 November using template matching analysis. The relocated seismicity catalog contains ∼4000 events with magnitudes between − 0.2 < M d < 3.6 "> −0.2< M d <3.6 . The swarm illuminated three sub-parallel, southwest striking and northwest dipping fault segments of km-scale dimension and thickness of up to 200 m. The segments contain coexisting populations of different focal-mechanisms, suggesting a complex fault zone structure with several sets of en échelon fault orientations. The migration of events along the three planar structures indicates a complex fluid and faulting interaction processes. We searched for correlations between seismic activity and tidal stresses and found some suggestive features, but nothing that we can be confident is statistically significant.

California↗

USGS2007

Assessment of Data for Use in the Development of Nutrient Criteria for Massachusetts Rivers and Streams

The U.S. Geological Survey synthesized, reviewed, and assessed Massachusetts water-quality data for use in the development of either numerical nutrient criteria for rivers and streams or a science-based framework for interpreting narrative criterial for nutrients. Water-quality data collected from 65 Massachusetts locations were selected to represent a wide range, but not a statistical selection, of drainage basins and high-, intermediate-, and low-nutrient ecoregions. Additional sites were selected at some locations to provide data to compare open- and closed-canopy effects on periphyton chlorophyll a concentrations. Nutrient and chlorophyll a concentrations are the primary focus of this study. Data for turbidity, color, dissolved oxygen, specific conductance, pH, and measures of aquatic-plant density also were examined. Water-quality data were analyzed by categories of year, ecoregion, drainage-basin size, Massachusetts nutrient ecoregion, presence of upstream wastewater dischargers, and canopy openness. Graphs and statistical analyses were used to evaluate data. The U.S. Environmental Protection Agency recommends the 25th-percentile value of a water-quality constituent as the numerical nutrient criterion when using all available data for the constituent. In this study of Massachusetts waters, the 25th percentiles of median values at all sampling stations were: total phosphorus, 0.019 milligram per liter (mg/L); total nitrogen, 0.44 (mg/L); and turbidity, 1.2 nephelometric turbidity units (NTU). When the data are sorted by the two USEPA nutrient ecoregions in Massachusetts (VIII and XIV), the new values are: for Ecoregion VIII, total phosphorus, 0.009 (mg/L); total nitrogen, 0.289 (mg/L); and turbidity, 1.7 NTU; for Ecoregion XIV, total phosphorus, 0.028 (mg/L); total nitrogen, 0.583 (mg/L); and turbidity, 3.1 NTU. For the three Massachusetts lake-based nutrient ecoregions, the values are: high-nutrient ecoregion, total phosphorus, 0.030 (mg/L); total nitrogen, 0.642 (mg/L); and turbidity, 1.5 NTU; intermediate-nutrient ecoregion, total phosphorus, 0.016 (mg/L); total nitrogen, 0.419 (mg/L); and turbidity, 1.1 NTU; and low-nutrient ecoregion, total phosphorus, 0.011 (mg/L); total nitrogen, 0.289 (mg/L); and turbidity, 0.7 NTU. In general, median nutrient concentrations were found to be higher in the three following categories of analysis than in their complementary groups: sites in USEPA nutrient Ecoregion XIV, sites downstream from major National Pollutant Discharge Elimination System-permitted wastewater dischargers, and sites in the Massachusetts high-nutrient ecoregion. The largest drainage-basin size class had higher median nitrogen (total and dissolved) concentrations than the smallest, but total median phosphorus concentrations were not significantly different. Median chlorophyll a concentrations did not vary significantly among the categories analyzed. The effects of open and closed canopies on median chlorophyll a concentrations were greater within groups defined by the categories used in this study than between the groups; open-canopy sites generally had higher median chlorophyll a concentrations than closed-canopy sites. More than 40 percent of the sampling stations were located downstream from major wastewater dischargers, and these dischargers were disproportionately located in USEPA Ecoregion XIV and the Massachusetts high-nutrient ecoregion and thus may constitute the same effect on water quality. A number of expected relations among parameters analyzed did not materialize. chlorophyll a did not correlate well with any other parameters. No strong relations among the categories and nutrient concentrations or canopy openness were apparent. The occurrence of antecedent flows exceeding mean annual discharges by 300 percent within 28 days of sample collection did not correlate with decreases in chlorophyll a concentrations that might have resulted from scouring associated with increasing velocities. No rel

Scientific Investigations Report↗

USGS2005

Factors affecting the toxicity of methylmercury injected into eggs

We developed a standardized protocol for comparing the sensitivities of the embryos of different bird species to methylmercury when methylmercury was injected into their eggs. During the course of developing this protocol, we investigated the effects of various factors on the toxicity of the injected methylmercury. Most of our experiments were done with chicken ( Gallus domesticus ), mallard ( Anas platyrhynchos ), and ring-necked pheasant ( Phasianus colchicus ) eggs, all of which were purchased in large numbers from game farms. A smaller amount of work was done with double-crested cormorant ( Phalacrocorax auritus ) eggs collected from the wild. Several solvents were tested, and corn oil at a rate of 1 μl/g egg contents was selected for the final standardized protocol because it had minimal toxicity to embryos and because methylmercury dissolved in corn oil yielded a dose–response curve in a range of egg concentrations that was similar to the range that causes reproductive impairment when the mother deposits methylmercury into her own eggs. The embryonic stage at which eggs were injected with corn oil altered mercury toxicity; at early stages, the corn oil itself was toxic. Therefore, in the final protocol we standardized the time of injection to occur when each species reached the morphologic equivalent of a 3-day-old chicken embryo. Although solvents can be injected directly into the albumen of an egg, high embryo mortality can occur in the solvent controls because of the formation of air bubbles in the albumen. Our final protocol used corn oil injections into the air cell, which are easier and safer than albumen injections. Most of the methylmercury, when dissolved in corn oil, injected into the air cell passes through the inner shell membrane and into the egg albumen. Most commercial incubators incubate eggs in trays with the air cell end of the egg pointing upward, but we discovered that mercury-induced mortality was too great when eggs were held in this orientation. In addition, some species of bird eggs require incubation on their sides with the eggs being rolled 180° for them to develop normally. Therefore, we adopted a procedure of incubating the eggs of all species on their sides and rolling them 180° every hour. Little has been published about the conditions of temperature, humidity, and the movements to which eggs of wild birds need to be subjected for them to hatch optimally under artificial incubation. Not unexpectedly, hatching success in an artificial incubator is generally less than what natural incubation by the parents can achieve. However, the survival of control embryos of most wild bird species was good (generally ≥ 80%) up to within 1 or 2 days of hatching when we incubated the eggs at 37.5°C (or 37.6°C for gallinaceous species) at a relative humidity that resulted in an approximate 15% to 16% loss in egg weight by the end of incubation and by incubating the eggs on their sides and rolling them 180°/h. To improve statistical comparisons, we used survival through 90% of incubation as our measurement to compare survival of controls with survival of eggs injected with graded concentrations of mercury.

Archives of Environmental Contamination and Toxico↗

USGS1972

The geologic setting of the Luna 16 landing site

The Luna 16 landing site is similar in its geologic setting to Apollos 11 and 12. All three sites are located on basaltic mare fill which occurs mostly within multi-ring basins formed by impact earlier in the moon's history. A regolith developed by impact bombardment is present at each of these sites. The regolith is composed mostly of locally derived volcanic material, but also contains exotic fine fragments that have been ballistically transported into the landing sites by large impact events which formed craters such as Langrenus and Copernicus. These exotic fragments probably consist mostly of earlier reworked multi-ring basin debris and, although not directly traceable to individual sources, they do represent a good statistical sample of the composition of most of the premare terrac regions.

Earth and Planetary Science Letters↗