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USGS2026

Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids

Objective We aimed to compare two machine learning approaches—boosted beta regression (BBR) and beta mixed model forest (BMF)—to a Bayesian mixed-effects beta regression (BME) for the prediction of rotary screw trap (RST) efficiency for out-migrating juvenile salmonids from environmental covariates. Methods We identified two machine learning approaches that shared the ability to model overdispersed probabilities. We compared the BBR and BMF machine learning models to a BME model to evaluate precision in detection probability prediction and model performance on bias in parameter estimation. We tested our three candidate models using a simulation study to understand the specific advantages and disadvantages of each when the data set was increasingly sparse and the capture probabilities were realistically small. We then applied the models to a case study of RST data from the Klamath River in California, United States. Results The BME and BMF outperformed BBR in all simulated scenarios, although the BMF displayed poor explanatory power. In the case study, the BME and BMF identified environmental covariates that predicted RST efficiency. Conclusions Using the BME as a benchmark for comparing machine learning approaches to trap efficiency modeling, our simulations and case study demonstrated that the BMF performed well and is a viable modeling approach with strong predictive power. The BME model would be the preferred modeling approach when its strong explanatory power is desired.

North American Journal of Fisheries Management↗

USGS1978

Accuracy of flood mapping

Information taken directly from published and unpublished reports was used to appraise the accuracy and the limitations of the three general flood-mapping methods: detailed, historical, and physiographic. In the appraisal, the probable nationwide average standard error of estimate for water depth and elevation in percentage of depth and in meters was determined for 100-year flood boundaries. Bias errors, users' errors, and certain time-variant errors were not. considered. The probable standard error for the detailed method is 23 percent. Based on 3.9 m as the national average 100-yr depth, the probable standard error of estimate is 0.9 m. The detailed method is applicable to a wide range of hydraulic and topographic conditions; it is the only method tested that is directly applicable to floodways analysis. The method requires detailed data and time-consuming analyses, however, and it has only limited application for determining flood elevations for sheet flow and for flow in channels having readily movable boundaries. The probable standard error for the historical method is 23 percent. Based on the 3.9-m average 100-yr depth, the standard error is 0.9 m. The historical method is applicable to a wide range of hydraulic and topographic conditions if specific data are available. The method is not applicable to floodways analysis, and it has only limited application for flow in moveable-boundary channels. The standard error for the physiographic method is 27 percent. In meters, the error is 1.1. .The physiographic method is simpler to apply than the other methods; however, it can be used only in natural channels having rigid boundaries. It is not applicable to sheet flow and to floodways analysis.

Journal of Research of the U.S. Geological Survey↗

USGS2012

Tectonic stresses in the lithosphere: constraints provided by the experimental deformation of rocks.

The strengths of rocks clearly place an upper limit on the stress that can be sustained by the upper half of the lithosphere. Laboratory data on rock rheology are generally lacking at intermediate temperatures and pressures on the important rock types expected in the lithosphere, so a definitive accounting of the strength distribution with depth in the upper lithosphere is presently unattainable. Analogies are drawn between the fragmentary strength data on silicates at intermediate temperature and the more extensive experimental data on marble and limestone, and several tentative conclusions are drawn: First, brittle processes, such as faulting and cataclasis, are expected to control rock strength at low pressures and temperatures. The strengths associated with these brittle mechanisms increase rapidly with increasing effective pressure and are relatively insensitive to temperature and strain rate. Second, the transitions between brittle and ductile processes occur at critical values of the least principal stress σ 3 . I suggest that the concept of the deformation mechanism map of Ashby (1972) be extended to brittle-ductile transitions by normalizing the applied differential stress σ by σ 3 , i.e., the transitions occur at critical values of σ/σ 3 . Third, the high temperature flow law of olivine, widely applied to problems involving flow in the asthenosphere, is inappropriate to the conditions of temperature found in the lithosphere, because different dislocation flow mechanisms dominate at low to intermediate temperatures. The fragmentary rheological data suggest the following rheological structure of the lithosphere where it is inelastically deforming: A rapid pressure-driven increase in rock strength with depth culminates with a shear strength maximum of up to 8 kbar at depths that depend on the state of stress and on the temperature distribution. A review of the mechanisms of weakening associated with water suggests that water weakening effects are probably not important in the oceanic lithosphere but are likely to be controlling in the continental crust.

Journal of Geophysical Research Solid Earth↗

USGS2016

Overwintering strategies of migratory birds: a novel approach for estimating seasonal movement patterns of residents and transients

Our understanding of movement patterns in wildlife populations has played an important role in current ecological knowledge and can inform landscape conservation decisions. Direct measures of movement can be obtained using marked individuals, but this requires tracking individuals across a landscape or multiple sites. We demonstrate how movements can be estimated indirectly using single-site, capture–mark–recapture (CMR) data with a multi-state open robust design with state uncertainty model (MSORD-SU). We treat residence and transience as two phenotypic states of overwintering migrants and use time- and state-dependent probabilities of site entry and persistence as indirect measures of movement. We applied the MSORD-SU to data on eight species of overwintering Neotropical birds collected in 14 countries between 2002 and 2011. In addition to entry and persistence probabilities, we estimated the proportions of residents at a study site and mean residence times. We identified overwintering movement patterns and residence times that contrasted with prior categorizations of territoriality. Most species showed an evidence of residents entering sites at multiple time intervals, with transients tending to enter between peak resident movement times. Persistence and the proportion of residents varied by latitude, but were not always positively correlated for a given species. Synthesis and applications . Our results suggest that migratory songbirds commonly move among habitats during the overwintering period. Substantial proportions of populations appear to be comprised of transient individuals, and residents tend to persist at specific sites for relatively short periods of time. This information on persistence and movement patterns should be explored for specific habitats to guide landscape management on the wintering grounds, such as determining which habitats are conserved or restored as part of certification programmes of tropical agroforestry crops. We suggest that research and conservation efforts on Neotropical migrant songbirds focus on identifying landscape configurations and regional habitat networks that support these diverse overwintering strategies to secure full life cycle conservation.

Journal of Applied Ecology↗

USGS2007

Concerns regarding a call for pluralism of information theory and hypothesis testing

1. Stephens et al. (2005) argue for 'pluralism' in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example. 2. I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches. 3. We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. 'no difference') is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past. 4. We clarify misconceptions presented by Stephens et al. (2005) . 5. We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob(Hj| data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data |H0). 6. Synthesis and applications . I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Journal of Applied Ecology↗

USGS2024

Simulation modeling to assess line transect distance sampling under a range of translocation scenarios

The accuracy of posttranslocation population monitoring methods is critical to assessing long-term success in translocation programs. Translocation can produce unique challenges to monitoring efforts; therefore, it is important to understand the flexibility and robustness of commonly used monitoring methods. In Florida, USA, thousands of gopher tortoises Gopherus polyphemus have been, and continue to be, translocated from development sites to permitted recipient sites. These recipient sites create a broad range of potential monitoring scenarios due to variability in soft-release strategies, habitat conditions, and population demographics. Line transect distance sampling is an effective method for monitoring natural tortoise populations, but it is currently untested for translocated populations. We therefore produced 3,024 individual-based, spatially explicit scenarios of translocated tortoise populations that differed in recipient site and tortoise population properties, based on real-world examples, literature review, and expert opinion. We virtually sampled simulated tortoise populations by using line transect distance sampling methods and built a Bayesian hierarchical model to estimate the population density for each simulation, which incorporated individual-level covariates (i.e., burrow width and burrow occupancy). Line transect distance sampling was largely appropriate for the conditions that typify gopher tortoise recipient sites, particularly when detection probability on the transect lines was greater than or equal to 0.85. Designing the layout of transects relative to the orientation of soft-release pens, to avoid possible sampling biases that lead to extreme outliers in estimates of tortoise densities, resulted in more accurate population estimates. We also suggest that use of individual-level covariates, applied using a Bayesian framework as demonstrated in our study, may improve the applicability of line transect distance sampling surveys in a variety of contexts and that simulation can be a powerful tool for assessing survey design in complex sampling situations.

Florida↗

USGS2023

Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection

Objective To evaluate the vulnerability of Bull Trout Salvelinus confluentus to potential climate changes across its range in Oregon, we compiled disparate expert knowledge of the distribution of spawning and rearing and combined these probabilistic statements as data along with documented records of breeding and rearing in a joint occupancy model. Methods The joint expert knowledge–occupancy model, which was based on discrete patches of cold water (≤13°C) suitable for spawning and rearing, permitted the association of true occupancy with climate and other explanatory variables while accounting for variation in detection probability. We then applied estimated relationships of patch occupancy with explanatory variables to projected coldwater patch configurations in the years 2040 and 2080. Result Projections of the kilometers of occupied coldwater patch in future decades suggest precipitous declines if current relationships of occupancy with environmental variables are maintained. Impacts of climate changes in future decades manifest directly through the outright loss of coldwater patches and increases in winter high flows but also indirectly by increased isolation. Conclusion Combining probabilistic statements of species distributions from knowledgeable experts with sparse occupancy data may be a robust and timely alternative when large numbers of repeated occupancy surveys are infeasible.

Oregon↗

USGS1983

A reconnaissance geochemical study of La Primavera geothermal area, Jalisco, Mexico

The Sierra La Primavera, a late Pleistocene rhyolitic caldera complex in Jalisco, Me??xico, contains fumaroles and large-discharge 65??C hot springs that are associated with faults related to caldera collapse and to later magma insurgence. The nearly-neutral, sodium bicarbonate, hot springs occur at low elevations at the margins of the complex, whereas the water-rich fumaroles are high and central. The Comisio??n Federal de Electricidad de Me??xico (CFE) has recently drilled two deep holes at the center of the Sierra (PR-1 and Pr-2) and one deep hole at the western margin. Temperatures as high as 285??C were encountered at 1160 m in PR-1, which produced fluids with 820 to 865 mg/kg chloride after flashing to one atmosphere. Nearby, PR-2 encountered temperatures to 307??C at 2000 m and yielded fluids with chloride contents fluctuating between 1100 and 1560 mg/kg after flashing. Neither of the high-temperature wells produced steam in commercial quantities. The well at the western margin of the Sierra produced fluids similar to those from the hot springs. The temperature reached a maximum of 100??C near the surface and decreased to 80??C at 2000 m. Various geothermometers (quartz conductive, Na/K, Na-K-Ca, ??18O(SO4-H2O) and D/H (steam-water) all yield temperatures of 170 ?? 20??C when applied to the hot spring waters, suggesting that these spring waters flow from a large shallow reservoir at this temperature. Because the hot springs are much less saline than the fluids recovered in PR-1 and PR-2, the mixed fluid in the shallow reservoir can contain no more than 10-20% deep fluid. This requires that most of the heat is transferred by steam. There is probably a thin vapor-dominated zone in the central part of the Sierra, through which steam and gases are transferred to the overlying shallow reservoir. Fluids from this reservoir cool from ???170??C to 65??C by conduction during the 5-7 km of lateral flow to the hot springs. ?? 1983.

Journal of Volcanology and Geothermal Research↗

USGS2015

Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite

Coal is a chemically complex commodity that often contains most of the natural elements in the periodic table. Coal constituents are conventionally grouped into four components (proximate analysis): fixed carbon, ash, inherent moisture, and volatile matter. These four parts, customarily measured as weight losses and expressed as percentages, share all properties and statistical challenges of compositional data. Consequently, adequate modeling should be done in terms of a logratio transformation, a requirement that is commonly overlooked by modelers. The transformation of choice is the isometric logratio transformation because of its geometrical and statistical advantages. The modeling is done through a series of realizations prepared by applying sequential simulation for the purpose of displaying the parts in maps incorporating uncertainty. The approach makes realistic assumptions and the results honor the data and basic considerations, such as percentages between 0 and 100, all four parts adding to 100% at any location in the study area, and a style of spatial fluctuation in the realizations equal to that of the data. The realizations are used to prepare different results, including probability distributions across a deposit, E-type maps displaying average properties, and probability maps summarizing joint fluctuations of several parts. Application of these maps to a lignite bed clearly delineates the deposit boundary, reveals a channel cutting across, and shows that the most favorable coal quality is to the north and deteriorates toward the southeast.

International Journal of Coal Geology↗

USGS2011

A Bayesian network to predict coastal vulnerability to sea level rise

Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (-1 < rate < 1 m/yr) or erosion (rate < -1 m/yr) tend to occur for two sets of input scenarios. Stable shoreline change rates occur mainly for low rates of relative sea level rise and occur in low-vulnerability geomorphic settings. Rates indicating erosion result for cases where the rate of relative sea level rise is high and moderate-to-high vulnerability geomorphic settings occur. In contrast, accretion (rate > 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions. Copyright ?? 2011 by the American Geophysical Union.

Journal of Geophysical Research F: Earth Surface↗

USGS2010

Predicting species distributions from checklist data using site-occupancy models

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. ?? 2010 Blackwell Publishing Ltd.

Journal of Biogeography↗

USGS2007

Effect of compost age and composition on the atrazine removal from solution

Compost samples from two composting facilities, the Urbana (Illinois) Landscape Recycling Center (ULRC) and Illinois State University (ISU), were selected to examine the effect of compost age on atrazine removal from solution. The ULRC samples were made from yard waste without an additional nitrogen source. The ISU samples were made from yard waste or sawdust with the addition of manure. The 6-month-old ULRC compost had the greater capacity to remove atrazine from solution, which we attributed to its greater organic carbon content. The addition of nitrate into ULRC compost could influence the extent of atrazine removal, but did not have a significant impact on atrazine removal when applied to ISU compost, probably because manure was added to the yard waste to produce the compost. For both ULRC and ISU samples, the presence of sodium azide inhibited atrazine removal, suggesting that microbial activity contributed to the atrazine removal. Metabolic analysis demonstrated that hydroxyatrazine was the major identified metabolite that accumulated in solution before significant ring mineralization could occur. When compared with the ISU compost, the ULRC compost sample had a greater capacity to remove atrazine from solution during the 120 days of study because of the larger humic acid content. The experimental results suggested that less-mature compost may be better suited for environmental applications such as removing atrazine from tile-drainage waters. ?? 2006 Elsevier B.V. All rights reserved.

Journal of Hazardous Materials↗

USGS2016

Calorific value and compositional ultimate analysis with a case study of a Texas lignite

Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an adequate modeling already described in a previous publication for the case of proximate analysis data. 1 Here we model the results of calorific value and ultimate analysis. We propose to use two different binary partitions, one per analysis, map the corresponding isometric logratio transformations, and backtransform the results. The methodology is illustrated using the same coal bed in the previous paper modeling proximate analysis data. Results are summarized using probability maps that, in the case of this deposit, show a prominent channel crossing the deposit and separating the best quality coal from that of lower quality.

International Journal of Coal Geology↗

USGS2022

Quantifying the relationship between prey density, livestock and illegal killing of leopards

Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events. Despite the importance of illegal killing of large carnivores in comparison with other causes of mortality, its relationship with potential drivers such as livestock density and wild prey abundance is rarely described. Using ranger-collected data (2007-2019) of leopard killing events and data on covariates (livestock density, wild prey abundance, road length, protected area size, elevation) across Iran, we applied a single-visit N-mixture model to jointly model variation in detection probability and expected annualized number of leopard killing events. Over the study period, we estimated 428 leopard mortalities (95% CI 184–1014), which was 45% larger than the observed number. Expected intensity of leopard killing was positively related to protected area size, livestock density and wild prey abundance. Detection of leopard killing was higher in areas with more developed road networks. Synthesis and applications: Ranger based monitoring data on poaching of carnivores are cost effective, but traditional analysis does not take into account imperfect detection. We show that innovative statistics (single-visit N-mixture modeling) can reliably quantify poaching events and address their drivers, at large geographical scales. We used the example of the Persian leopard across Iran, but our approach is also applicable to understand killing dynamics of other species. Results suggest that a high frequency of leopard killing is likely to occur in areas with > 100 livestock per km 2 and > 450 individuals of wild prey per km 2 . This highlights the need for improved management of livestock grazing and effective measures around high-risk protected areas to mitigate human-leopard conflict and reduce killing of leopards.

Journal of Applied Ecology↗

USGS2015

Toward a mechanistic understanding of human-induced rapid environmental change: A case study linking energy development, avian nest predation, and predators

Demographic consequences of human-induced rapid environmental change (HIREC) have been widely documented for many populations. The mechanisms underlying such patterns, however, are rarely investigated and yet are critical to understand for effective conservation and management. We investigated the mechanisms underlying reduced avian nest survival with intensification of natural gas development, an increasing source of human-induced rapid environmental change globally. We tested the hypothesis that energy development increased the local activity of important nest predator species, thereby elevating nest predation rates. During 2011–2012, we surveyed predators and monitored 668 nests of Brewer's sparrows Spizella breweri (BRSP), sagebrush sparrows Artemisiospiza nevadensis (SASPs) and sage thrashers Oreoscoptes montanus (SATHs) breeding at twelve sites spanning a gradient of habitat loss from energy development in western Wyoming, USA. Nine species, representing four mammalian and three avian families, were video-recorded depredating eggs and nestlings. Important nest predator species differed across songbird species, despite similar nesting habitats. Approximately 75% of depredation events were by rodents. Consistent with our predictions, detections of most rodent nest predators increased with surrounding habitat loss due to natural gas development, which was associated with increased probability of nest predation for our three focal bird species. An altered nest predator assemblage was therefore at least partly responsible for elevated avian nest predation risk in areas with more surrounding energy development. Synthesis and applications . We demonstrate one mechanism, that is the local augmentation of predators, by which human-induced rapid environmental change can influence the demography of local populations. Given the accelerating trajectory of global energy demands, an important next step will be to understand why the activity and/or abundance of rodent predators increased with surrounding habitat loss from energy development activities.

Journal of Applied Ecology↗

USGS2011

Discrete choice modeling of shovelnose sturgeon habitat selection in the Lower Missouri River

Substantive changes to physical habitat in the Lower Missouri River, resulting from intensive management, have been implicated in the decline of pallid ( Scaphirhynchus albus ) and shovelnose ( S. platorynchus ) sturgeon. To aid in habitat rehabilitation efforts, we evaluated habitat selection of gravid, female shovelnose sturgeon during the spawning season in two sections (lower and upper) of the Lower Missouri River in 2005 and in the upper section in 2007. We fit discrete choice models within an information theoretic framework to identify selection of means and variability in three components of physical habitat. Characterizing habitat within divisions around fish better explained selection than habitat values at the fish locations. In general, female shovelnose sturgeon were negatively associated with mean velocity between them and the bank and positively associated with variability in surrounding depths. For example, in the upper section in 2005, a 0.5 m s −1 decrease in velocity within 10 m in the bank direction increased the relative probability of selection 70%. In the upper section fish also selected sites with surrounding structure in depth (e.g., change in relief). Differences in models between sections and years, which are reinforced by validation rates, suggest that changes in habitat due to geomorphology, hydrology, and their interactions over time need to be addressed when evaluating habitat selection. Because of the importance of variability in surrounding depths, these results support an emphasis on restoring channel complexity as an objective of habitat restoration for shovelnose sturgeon in the Lower Missouri River.

Kansas, Missouri, Nebraska, South Dakota↗

USGS2023

Territories within groups: The dynamic competition of drift-feeding juvenile Chinook salmon in 3-dimensional space

Salmonid populations are often regulated by territorial competition among juveniles for food and space. In the canonical view, salmonid territories are spaced horizontally across the river bottom in a 2-D mosaic. However, some juveniles instead feed in tight, three-dimensional (3-D) social groups. To investigate whether territoriality is possible within such groups, we applied a new concept—the momentary home range—to quantify the size, exclusivity, and temporal dynamics of 3-D space use by juvenile Chinook Salmon ( Oncorhynchus tshawytscha ) in the Chena River, Alaska. Individual strategies spanned a broad continuum of exclusivity and stationarity. However, some of the largest, most dominant fish in each group aggressively defended stationary, exclusive feeding spaces and thus were unambiguously territorial. Transient floaters entered and left the group quickly. A majority of fish were not aggressive but nevertheless occupied exclusive, stationary spaces that probably function as territories with regard to resource distribution and population regulation. The presence of territoriality within social groups, in a 3-D configuration, expands the known domain of this important behavior.

Alaska↗

USGS1985

Comparative study of aggregations under different dependency assumptions for assessment of undiscovered recoverable oil resources in the world

The U.S. Geological Survey assessed all significant sedimentary basins in the world for undiscovered conventionally recoverable crude-oil resources. Probabilistic methodology was applied to each basin assessment to produce estimates in the form of probability distributions. Basin probability distributions were computer aggregated to produce resource estimates for the entire world. Aggregation was approximated by a three-parameter lognormal distribution by combining the first three central moments of basin distributions. For purposes of experiment and study, world aggregation was conducted under four different sets of assumptions. The four cases are (1) dependent assessments of all basins, (2) dependent assessments within continental areas, but independent assessments among continental areas, (3) dependent assessments within countries, but independent assessments among countries, and (4) independent assessments of all basins. Mean estimate remained the same in all four cases, but the width of interval estimate formed using the 95th and 5th fractiles decreased with reduced dependency in going from first to fourth case. ?? 1985 Plenum Publishing Corporation.

Journal of the International Association for Mathe↗