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At least 37 records · Page 2Linked to original sources
USGS2013

Smolt physiology and endocrinology

Hormones play a critical role in maintaining body fluid balance in euryhaline fishes during changes in environmental salinity. The neuroendocrine axis senses osmotic and ionic changes, then signals and coordinates tissue-specific responses to regulate water and ion fluxes. Rapid-acting hormones, e.g. angiotensins, cope with immediate challenges by controlling drinking rate and the activity of ion transporters in the gill, gut, and kidney. Slow-acting hormones, e.g. prolactin and growth hormone/insulin-like growth factor-1, reorganize the body for long-term acclimation by altering the abundance of ion transporters and through cell proliferation and differentiation of ionocytes and other osmoregulatory cells. Euryhaline species exist in all groups of fish, including cyclostomes, and cartilaginous and teleost fishes. The diverse strategies for responding to changes in salinity have led to differential regulation and tissue-specific effects of hormones. Combining traditional physiological approaches with genomic, transcriptomic, and proteomic analyses will elucidate the patterns and diversity of the endocrine control of euryhalinity.

Book chapter↗
USGS1997

Evaluation of semen from nondomestic birds

Aspects of poultry Al technology are applicable to nondomestic birds. However, modifications in the methods of semen collection, evaluation, and insemination are often necessary to accommodate either the bird's size, sperm numbers, or. female anatomy. This section provides a brief overview of procedures used to evaluate semen from nondomestic birds. Unless specified, materials, reagents, etc., are identical to those used in evaluating poultry semen (see appropriate chapters).

Book chapter↗
USGS2012

Volcanoes: observations and impact

Volcanoes are critical geologic hazards that challenge our ability to make long-term forecasts of their eruptive behaviors. They also have direct and indirect impacts on human lives and society. As is the case with many geologic phenomena, the time scales over which volcanoes evolve greatly exceed that of a human lifetime. On the other hand, the time scale over which a volcano can move from inactivity to eruption can be rather short: months, weeks, days, and even hours. Thus, scientific study and monitoring of volcanoes is essential to mitigate risk. There are thousands of volcanoes on Earth, and it is impractical to study and implement ground-based monitoring at them all. Fortunately, there are other effective means for volcano monitoring , including increasing capabilities for satellite-based technologies.

Book chapter↗
USGS2020

Wildfire and landscape change

Wildfire is a worldwide phenomenon that is expected to increase in extent and severity in the future, due to fuel accumulations, shifting land management practices, and climate change. It immediately affects the landscape by removing vegetation, depositing ash, influencing water-repellent soil formation, and physically weathering boulders and bedrock. These changes typically lead to increased erosion through sheetwash, rilling, dry ravel, and increased mass movement in the form of floods, debris flow, rockfall, and landslides. These process changes bring about landform changes as hillslopes are lowered and stream channels aggrade or incise at increased rates. Furthermore, development of alluvial fans, debris fans, and talus cones are enhanced. The window of disturbance to the landscape caused by wildfire is typically on the order of 3–4 years, with some effects persisting up to 30 years.

Book chapter↗
USGS2005

Estimating the number of animals in wildlife populations

INTRODUCTION In 1938, Howard M. Wight devoted 9 pages, which was an entire chapter in the first wildlife management techniques manual, to what he termed 'census' methods. As books and chapters such as this attest, the volume of literature on this subject has grown tremendously. Abundance estimation remains an active area of biometrical research, as reflected in the many differences between this chapter and the similar contribution in the previous manual. Our intent in this chapter is to present an overview of the basic and most widely used population estimation techniques and to provide an entree to the relevant literature. Several possible approaches could be taken in writing a chapter dealing with population estimation. For example, we could provide a detailed treatment focusing on statistical models and on derivation of estimators based on these models. Although a chapter using this approach might provide a valuable reference for quantitative biologists and biometricians, it would be of limited use to many field biologists and wildlife managers. Another approach would be to focus on details of actually applying different population estimation techniques. This approach would include both field application (e.g., how to set out a trapping grid or conduct an aerial survey) and detailed instructions on how to use the resulting data with appropriate estimation equations. We are reluctant to attempt such an approach, however, because of the tremendous diversity of real-world field situations defined by factors such as the animal being studied, habitat, available resources, and because of our resultant inability to provide detailed instructions for all possible cases. We believe it is more useful to provide the reader with the conceptual basis underlying estimation methods. Thus, we have tried to provide intuitive explanations for how basic methods work. In doing so, we present relevant estimation equations for many methods and provide citations of more detailed treatments covering both statistical considerations and field applications. We have chosen to present methods that are representative of classes of estimators, rather than address every available method. Our hope is that this chapter will provide the reader with enough background to make an informed decision about what general method(s) will likely perform well in any particular field situation. Readers with a more quantitative background may then be able to consult detailed references and tailor the selected method to suit their particular needs. Less quantitative readers should consult a biometrician, preferably one with experience in wildlife studies, for this 'tailoring,' with the hope they will be able to do so with a basic understanding of the general method, thereby permitting useful interaction and discussion with the biometrician. SUMMARY Estimating the abundance or density of animals in wild populations is not a trivial matter. Virtually all techniques involve the basic problem of estimating the probability of seeing, capturing, or otherwise detecting animals during some type of survey and, in many cases, sampling concerns as well. In the case of indices, the detection probability is assumed to be constant (but unknown). We caution against use of indices unless this assumption can be verified for the comparison(s) of interest. In the case of population estimation, many methods have been developed over the years to estimate the probability of detection associated with various kinds of count statistics. Techniques range from complete counts, where sampling concerns often dominate, to incomplete counts where detection probabilities are also important. Some examples of the latter are multiple observers, removal methods, and capture-recapture. Before embarking on a survey to estimate the size of a population, one must understand clearly what information is needed and for what purpose the information will be used. The key to derivin

Book chapter↗
USGS2021

Restoration of mangrove forest

Mangrove forests occur worldwide along tropical coasts in inundated soils where primary production and anaerobic conditions contribute to the building of soil organic matter (Also see Mangroves Hot-spot, Volume 2). Note that peat may accumulate in certain coastal mangrove (Middleton and McKee, 2001). The actual amount of soil organic matter stored in these wetlands depends on the balance between primary production and decomposition processes (Middleton and McKee, 2001; Kolka et al., 2018; Middleton, 2020). The restoration of mangroves can increase carbon stocks both in soil and aboveground biomass (Wickland et al., 2013; Chimner et al., 2017; Friess et al., 2019). While tropical inland peatland forests may have higher carbon sequestration rates than mangrove swamps, methane (CH4) emissions are generally lower in mangrove swamp, so that these wetlands have greater carbon sequestration potential (Kolka et al., 2018; Al-Haj and Fulweiler, 2020). Mangroves and forested boreal and temperate peatlands tend to store more carbon than non-forested peatlands (Kolka et al., 2018).

Book chapter↗
USGS2018

Climate change science and modeling

This chapter provides a brief background on climate change science, climate simulation models, and models that project the impacts of changes in climate on tree species and ecosystems. Throughout the chapter, boxes list resources for more information on each topic. A more detailed scientific review of climate change science, trends, and modeling can be found in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (IPCC 2014), and the Fourth National Climate Assessment (U.S. Global Climate Research Program [USGCRP] 2017).

Delaware, Maryland, New Jersey, New York, Pennsylv↗
USGS2016

Modeling abundance using hierarchical distance sampling

In this chapter, we provide an introduction to classical distance sampling ideas for point and line transect data, and for continuous and binned distance data. We introduce the conditional and the full likelihood, and we discuss Bayesian analysis of these models in BUGS using the idea of data augmentation, which we discussed in Chapter 7. We then extend the basic ideas to the problem of hierarchical distance sampling (HDS), where we have multiple point or transect sample units in space (or possibly in time). The benefit of HDS in practice is that it allows us to directly model spatial variation in population size among these sample units. This is a preeminent concern of most field studies that use distance sampling methods, but it is not a problem that has received much attention in the literature. We show how to analyze HDS models in both the unmarked package and in the BUGS language for point and line transects, and for continuous and binned distance data. We provide a case study of HDS applied to a survey of the island scrub-jay on Santa Cruz Island, California.

Book chapter↗
USGS2018

Defining blue carbon: The emergence of a climate context for coastal carbon dynamics

Blue Carbon Ecosystems (BCEs) are defined as coastal wetland ecosystems with manageable and atmospherically significant carbon stocks and fluxes. Policy and management opportunities have promoted the emergence of blue carbon as a concept and spurred scientific interest to reduce uncertainties in coastal carbon budgets. The four major BCEs are generally classified by their plant communities: tidal marshes, tidal freshwater forests, mangroves, and seagrass meadows.

Book chapter↗
USGS2013

Managing the effects of endocrine disrupting chemicals in wastewater-impacted streams

A revolution in analytical instrumentation circa 1920 greatly improved the ability to characterize chemical substances. This analytical foundation resulted in an unprecedented explosion in the design and production of synthetic chemicals during and post-World War II. What is now often referred to as the 2nd Chemical Revolution has provided substantial societal benefits; with modern chemical design and manufacturing supporting dramatic advances in medicine, increased food production, and expanding gross domestic products at the national and global scales as well as improved health, longevity, and lifestyle convenience at the individual scale. Presently, the chemical industry is the largest manufacturing sector in the United States (U.S.) and the second largest in Europe and Japan, representing approximately 5% of the Gross Domestic Product (GDP) in each of these countries. At the turn of the 21st century, the chemical industry was estimated to be worth more than $1.6 trillion and to employ over 10 million people, globally. During the first half of the 20th century, the chemical sector expanded rapidly, the chemical industry enjoyed a generally positive status in society, and chemicals were widely appreciated as fundamental to individual and societal quality of life. Starting in the 1960s, however, the environmental costs associated with the chemical industry increasingly became the focus, due in part to the impact of books like “Silent Spring” and “Our Stolen Future” and to a number of highly publicized environmental disasters. Galvanizing chemical industry disasters included the 1976 dioxin leak north of Milan, Italy, the Love Canal evacuations in Niagara, New York beginning in 1978, and the Union Carbide leak in Bhopal, India in 1984. Understanding the environmental impact of synthetic compounds is essential to any informed assessment of net societal benefit, for the simple reason that any chemical substance that is in commercial production or use will eventually find its way to the environment. Not surprisingly given the direct link to profits, manufacturers intensely investigate and routinely document the potential benefits of new chemicals and chemical products. In contrast, the environmental risks associated with chemical production and uses are often investigated less intensely and are poorly communicated. An imbalance in the risk-benefit analysis of any synthetic chemical substance or naturally occurring chemical, which presence and concentration in the environment largely reflects human activities and management, is a particular concern owing to the fundamental link between chemistry and biology. Biological organisms are intrinsically a homeostatic balance of innumerable internal and external chemical interactions and, thus, inherently sensitive to changes in the external chemical environment.

Book chapter↗
USGS2012

Uncertainty

Management decisions will often be directly informed by model predictions. However, we now know there can be no expectation of a single ‘true’ model; thus, model results are uncertain. Understandable reporting of underlying uncertainty provides necessary context to decision-makers, as model results are used for management decisions. This, in turn, forms a mechanism by which groundwater models inform a risk-management framework because uncertainty around a prediction provides the basis for estimating the probability or likelihood of some event occurring. Given that the consequences of management decisions vary, it follows that the extent of and resources devoted to an uncertainty analysis may depend on the consequences. For events with low impact, a qualitative, limited uncertainty analysis may be sufficient for informing a decision. For events with a high impact, on the other hand, the risks might be better assessed and associated decisions made using a more robust and comprehensive uncertainty analysis. The purpose of this chapter is to provide guidance on uncertainty analysis through discussion of concepts and approaches, which can vary from heuristic (i.e. the modeller’s assessment of prediction uncertainty based on trial and error and experience) to a comprehensive, sophisticated, statistics-based uncertainty analysis. Most of the material presented here is taken from Doherty et al. (2010) if not otherwise cited. Although the treatment here is necessarily brief, the reader can find citations for the source material and additional references within this chapter.

Book chapter↗
USGS2016

Streamflow data

The importance of streamflow data to the world’s economy, environmental health, and public safety continues to grow as the population increases. The collection of streamflow data is often an involved and complicated process. The quality of streamflow data hinges on such things as site selection, instrumentation selection, streamgage maintenance and quality assurance, proper discharge measurement techniques, and the development and continued verification of the streamflow rating. This chapter serves only as an overview of the streamflow data collection process as proper treatment of considerations, techniques, and quality assurance cannot be addressed adequately in the space limitations of this chapter. Readers with the need for the detailed information on the streamflow data collection process are referred to the many references noted in this chapter.

Book chapter↗
USGS2019

Coelomic disorders of fishes

Dropsy is a commonly applied term for coelomic distention due to ascites, or the effusion and collection of fluid freely throughout the coelomic cavity. Dropsy, or ascites, is generally a sign of another ongoing disease process, oftentimes one that is multisystemic and impacting coelomic organs and tissues. Dropsy may be caused by a variety of potential etiological agents, both infectious and noninfectious. Stressors such as rapid change in water temperature may predispose fish to bacterial diseases associated with dropsy. Clinically affected fish display coelomic distension of varying degrees of severity. Generally considered a disease syndrome similar to dropsy, affecting specifically Malawi cichlids, a popular group of ornamental fish among aquarium hobbyists. Water belly occurs among salt water pen-reared salmonid fish, including Atlantic salmon, Chinook salmon and rainbow trout. Dietary changes such as reduction of the feeding rate have been reported to improve the condition among affected fish.

Book chapter↗
USGS2009

Eruption-related lahars and sedimentation response downstream of Mount Hood: Field guide to volcaniclastic deposits along the Sandy River, Oregon

Late Holocene dome-building eruptions at Mount Hood during the Timberline and Old Maid eruptive periods resulted in numerous dome-collapse pyroclastic flows and lahars that moved large volumes of volcaniclastic sediment into temporary storage in headwater canyons of the Sandy River. During each eruptive period, accelerated sediment loading to the river through erosion and remobilization of volcanic fragmental debris resulted in very high sediment-transport rates in the Sandy River during rain- and snowmelt-induced floods. Large sediment loads in excess of the river's transport capacity led to channel aggradation, channel widening, and change to a braided channel form in the lowermost reach of the river, between 61 and 87 km downstream from the volcano. The post-eruption sediment load moved as a broad bed-material wave, which in the case of the Old Maid eruption took ~2 decades to crest 83 km downstream. Maximum post-eruption aggradation levels of at least 28 and 23 m were achieved in response to Timberline and Old Maid eruptions. In each case, downstream aggradation cycles were initiated by lahars, but the bulk of the aggradation was achieved by fluvial sediment transport and deposition. When the high rates of sediment supply began to diminish, the river degraded, incising the channel fills and forming progressively lower sets of degradational terraces. A variety of debris-flow, hyperconcentrated-flow, and fluvial (upper and lower flow regime) deposits record the downstream passage of the sediment waves that were initiated by these eruptions. The deposits also presage a hazard that may be faced by communities along the Sandy River when volcanic activity at Mount Hood resumes.

Oregon↗