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At least 1,729 records · Page 96Linked to original sources
USGS2023

Nest traits and major flooding events influence nest survival of Emperor Geese while regional environmental variation linked to climate does not

The reproductive ecology of geese that breed in the Arctic and subarctic is likely susceptible to the effects of climate change, which is projected to alter the environmental conditions of northern latitudes. Nest survival is an important component of productivity in geese; however, the effects of regional environmental conditions on nest survival are not well understood for some species, including the Emperor Goose ( Anser canagicus ), a species of conservation concern that is endemic to the Bering Sea region. We estimated nest survival and examined how indices of regional environmental conditions, nest traits (nest age, initiation date, and maximum number of eggs in the nest), and researcher disturbance influenced daily survival probability (DSP) of Emperor Goose nests using hierarchical models and 24 years of nest monitoring data (1994–2017) from the Yukon–Kuskokwim Delta (Y–K Delta) in western Alaska. Our results indicate that overall nest survival was generally high (µ = 0.766, 95% CRI: 0.655–0.849) and ranged from 0.327 (95% CRI: 0.176–0.482) in 2013 to 0.905 (95% CRI: 0.839–0.953) in 1995. We found that DSPs of nests were influenced by nest traits, negatively influenced by major tidal flooding events and by researcher disturbance, but were not influenced by regional indices of spring timing, temperature and precipitation during nesting, or fox and vole abundance on the Y–K Delta. However, the number of nests found each year was negatively related to our index of fox abundance, suggesting nests that failed as a result of fox predation may have never been discovered due to our limited nest-searching efforts during egg laying. Our results suggest that regional environmental variation had minimal influence on the nest survival of Emperor Geese, although major flooding events were important. Nevertheless, we suspect that within-year variation in local weather conditions and local abundance of predators and alternative prey may be important and should be considered in future studies.

Alaska↗
USGS2011

Engineering a future for amphibians under climate change

1. Altered global climates in the 21st century pose serious threats for biological systems and practical actions are needed to mount a response for species at risk. 2. We identify management actions from across the world and from diverse disciplines that are applicable to minimizing loss of amphibian biodiversity under climate change. Actions were grouped under three thematic areas of intervention: (i) installation of microclimate and microhabitat refuges; (ii) enhancement and restoration of breeding sites; and (iii) manipulation of hydroperiod or water levels at breeding sites. 3. Synthesis and applications. There are currently few meaningful management actions that will tangibly impact the pervasive threat of climate change on amphibians. A host of potentially useful but poorly tested actions could be incorporated into local or regional management plans, programmes and activities for amphibians. Examples include: installation of irrigation sprayers to manipulate water potentials at breeding sites; retention or supplementation of natural and artificial shelters (e.g. logs, cover boards) to reduce desiccation and thermal stress; manipulation of canopy cover over ponds to reduce water temperature; and, creation of hydrologoically diverse wetland habitats capable of supporting larval development under variable rainfall regimes. We encourage researchers and managers to design, test and scale up new initiatives to respond to this emerging crisis.

Journal of Applied Ecology↗
USGS2016

Ecoregions of California

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000). The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014). California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014). The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities. The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.

California↗
USGS2010

Nitrogen and phosphorus in the Upper Mississippi River: Transport, processing, and effects on the river ecosystem

Existing research on nutrients (nitrogen and phosphorus) in the Upper Mississippi River (UMR) can be organized into the following categories: (1) Long-term changes in nutrient concentrations and export, and their causes; (2) Nutrient cycling within the river; (3) Spatial and temporal patterns of river nutrient concentrations; (4) Effects of elevated nutrient concentrations on the river; and (5) Actions to reduce river nutrient concentrations and flux. Nutrient concentration and flux in the Mississippi River have increased substantially over the last century because of changes in land use, climate, hydrology, and river management and engineering. As in other large floodplain rivers, rates of processes that cycle nitrogen and phosphorus in the UMR exhibit pronounced spatial and temporal heterogeneity because of the complex morphology of the river. This spatial variability in nutrient processing creates clear spatial patterns in nutrient concentrations. For example, nitrate concentrations generally are much lower in off-channel areas than in the main channel. The specifics of in-river nutrient cycling and the effects of high rates of nutrient input on UMR have been less studied than the factors affecting nutrient input to the river and transport to the Gulf of Mexico, and important questions concerning nutrient cycling in the UMR remain. Eutrophication and resulting changes in river productivity have only recently been investigated the UMR. These recent studies indicate that the high nutrient concentrations in the river may affect community composition of aquatic vegetation (e. g., the abundance of filamentous algae and duckweeds), dissolved oxygen concentrations in off-channel areas, and the abundance of cyanobacteria. Actions to reduce nutrient input to the river include changes in land-use practices, wetland restoration, and hydrological modifications to the river. Evidence suggests that most of the above methods can contribute to reducing nutrient concentration in, and transport by, the UMR, but the impacts of mitigation efforts will likely be only slowly realized. ?? USGS, US Government 2010.

Hydrobiologia↗
USGS2021

Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach

A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics , and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.

North Carolina, South Carolina, Virginia↗
USGS2017

50,000 years of vegetation and climate history on the Colorado Plateau, Utah and Arizona, USA

Sixty packrat middens were collected in Canyonlands and Grand Canyon National Parks, and these series include sites north of areas that produced previous detailed series from the Colorado Plateau. The exceptionally long time series obtained from each of three sites (> 48,000 14 C yr BP to present) include some of the oldest middens yet discovered. Most middens contain a typical late-Wisconsinan glaciation mixture of mesic and xeric taxa, evidence that plant species responded to climate change by range adjustments of elevational distribution based on individual criteria. Differences in elevational range from today for trees and shrubs ranged from no apparent change to as much as 1200 m difference. The oldest middens from Canyonlands NP, however, differ in containing strictly xeric assemblages, including middens incorporating needles of Arizona single-leaf pinyon, far north of its current distribution. Similar-aged middens from the eastern end of Grand Canyon NP contain plants more typical of glacial climates, but also contain fossils of one-seed juniper near its current northern limit in Arizona. Holocene middens reveal the development of modern vegetation assemblages on the Colorado Plateau, recording departures of mesic taxa from low elevation sites, and the arrival of modern dominant components much later.

Arizona, Utah↗
USGS2025

Public supply water delivery analysis and estimation for the conterminous United States

Public supply water withdrawals represent 14% of all withdrawals in the conterminous United States (CONUS), supplying approximately 87% of the population with fresh water. Deliveries for public water supply are crucial for associating water use amounts with populations because they often differ from total withdrawals due to wholesales, transfers, losses, and other factors. Understanding these differences helps identify the drivers for each type of delivery. The goal of this study was to compile all available public water supply delivery data for the CONUS and develop a data-driven model to estimate deliveries for all water service areas within the CONUS. Annual deliveries were estimated between 2010 and 2020, encompassing total water deliveries; combined commercial, industrial, and institutional deliveries (CII); and domestic deliveries. Data were compiled for 2,744 water service areas to produce the most comprehensive public water supply delivery data set for the CONUS to date. Three ensemble modeling approaches were developed to estimate total, CII, and domestic per capita (DPC) deliveries using a gradient boosted regression tree modeling approach. Estimates of daily domestic and CII per capita deliveries were generated from these models for approximately 18,800 water service areas, covering most public water systems in the CONUS. Domestic delivery was found to be lowest in the midwestern region and higher in the southern and southwest regions of the United States. Results indicate that climate and land use can be associated with regional differences in DPC delivery. Population metrics and land use were identified as significant contributors to CII delivery estimates.

conterminous United States↗
USGS2018

Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales

Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl- a ), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl- a , nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl- a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl- a to predictor variables quarter) and explained ~ 30% of variation in Chl- a . Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl- a , and that nearly a third of global variability in Chl- a may be explained using hydrogeomorphic and climate variables.

Inland Waters↗
USGS2011

Global amphibian declines: perspectives from the United States and beyond

Over recent decades, amphibians have experienced population declines, extirpations and species-level extinctions at an alarming rate. Numerous potential etiologies for amphibian declines have been postulated including climate and habitat degradation. Other potential anthropogenic causes including overexploitation and the frequent introductions of invasive predatory species have also been blamed for amphibian declines. Still other underlying factors may include infectious diseases caused by the chytrid fungus Batrachochytrium dendrobatidis, pathogenic viruses (Ranavirus), and other agents. It is nearly certain that more than one etiology is to blame for the majority of the global amphibian declines, and that these causal factors include some combination of climatological or physical habitat destabilization and infectious disease, most notably chytridiomycosis. Scientific research efforts are aimed at elucidating these etiologies on local, regional, and global scales that we might better understand and counteract the driving forces behind amphibian declines. Conservation efforts as outlined in the Amphibian Conservation Action Plan of 2005 are also being made to curtail losses and prevent further extinctions wherever possible.

Conference Paper↗
USGS2009

Reply to the Comment on "Wave climate, sediment supply and the depth of the sand-mud transition: A global survey" by D.A. George and P.S. Hill [Marine Geology 254 (2008) 121-128]

An analysis of concepts presented by George and Hill [George, D.A., Hill, P.S., 2008. Wave climate, sediment supply and the depth of the sand-mud transition: A global survey. Marine Geology, 254, 121-128.] regarding the depth of the sand-mud transition (h SMT ) was performed by Guill??n and Jim??nez [Jorge Guill??n and Jos?? A. Jim??nez, Comment on "Wave climate, sediment supply and the depth of the sand-mud transition: A global survey" by D.A. George and P.S. Hill [Marine Geology 254 (2008) 121-128], Marine Geology, in press]. We are pleased that our proposed definition of the h SMT was confirmed to be appropriate. We are encouraged that the authors agree that wave period and wave height should both be used to determine h SMT as we demonstrated in our Eq. (1), which calculates the bed shear stress at h SMT . More in-depth research should focus on characterizing the role of sediment supply in determining h SMT . ?? 2009 Elsevier B.V. All rights reserved.

Marine Geology↗
USGS2021

A machine learning approach to modeling streamflow with sparse data in ungaged watersheds on the Wyoming Range, Wyoming, 2012–17

Scant availability of streamflow data can impede the utility of streamflow as a variable in ecological models of aquatic and terrestrial species, especially when studying small streams in watersheds that lack streamgages. Streamflow data at fine resolution and broad extent were needed by collaborators for ecological research on small streams in several ungaged watersheds of southwestern Wyoming, where streamflow data are sparse. To improve the utility of sparse streamflow data to ecological research in ungaged watersheds, we developed a machine learning approach in R for modeling spatially and temporally continuous monthly streamflow from 2012 through 2017 in three semiarid montane-steppe watersheds (with drainage areas of 26–55 square miles and mean elevations of 8,031–8,455 feet) on the Wyoming Range in the upper Green River Basin. A machine learning streamflow (MLFLOW) model was calibrated and validated with 971 discrete streamflow observations and 24 static and dynamic predictor variables derived from geospatial and time series data on climatic, physiographic, and anthropogenic characteristics affecting streamflow. The predictor variables were temporally and spatially conditioned to amplify the relation of predictor variables to monthly streamflow. The MLFLOW model had satisfactory agreement between observed and predicted streamflow (coefficient of determination [ R 2 ]=0.80, Nash-Sutcliffe efficiency [NSE]=0.79, NSE with log-transformed data [logNSE]=0.82, and percent bias [PBIAS]=0.7 percent). NSE and logNSE indicated the MLFLOW model performed equally well for high and low flows, and PBIAS indicated the MLFLOW model did not overpredict or underpredict monthly streamflow. Streamflow predictions seemed to well represent the annual hydrograph within the study area during the study period. The most important variables (statistically important in the MLFLOW model) for explaining monthly streamflow were temporally and spatially conditioned dynamic climatic variables, mostly precipitation and snow water equivalent. Importance of the static and dynamic variables did not differ substantially among the three watersheds but differed considerably among the 6 years. Monthly streamflow increased with increasing precipitation, snow water equivalent, and drainage area but decreased with increasing forest cover, elevation, evapotranspiration, and temperature. The MLFLOW model was most sensitive to selection of dynamic climatic variables. Unconditioned dynamic climatic variables alone explained 54 percent of the variance ( R 2 =0.54) in monthly streamflow, whereas adding static physiographic and anthropogenic variables only explained 12 percent more of the variance ( R 2 =0.66). Also, spatial conditioning of all variables together with temporal conditioning of dynamic variables increased the variance explained in the MLFLOW model by another 14 percent ( R 2 =0.80). The MLFLOW model also had greater sensitivity to temporal than to spatial differences in the data. For the MLFLOW model trained with observations from all watersheds and years or for models trained with observations from all except one watershed or 1 year left out sequentially, performance was better in testing on observations from each watershed than from each year separately. Also, performance was better for models fitted to fewer sites than to fewer months of observations. The greatest utility of the modeling approach is the ease of use and the speed of processing input data, running the model, and interpreting the model output, whereas the greatest limitation is the need for spatially and temporally representative streamflow observations to drive the model. Although familiarity with R is necessary, only a working knowledge of hydrology (for selecting appropriate predictor variables and evaluating the quality of streamflow observations) and a rudimentary understanding of machine learning models are needed. Therefore, this modeling approach is practicable for other scientists who work with water but who are not hydrologists.

Wyoming↗
USGS2014

Park Break: collaborative opportunity established for graduate students

Among the many topics discussed during the 2007-2008 George Wright Society (GWS) board meetings was the subject of how to inspire students seeking careers in science and natural resource management to consider the Department of Interior (DOI) in general, and the National Park Service (NPS) and the US Geological Survey (USGS) in particular, as good options for future employment. Board members participating in these discussions included Suzette Kimball, now acting director of USGS, and Gillian Browser, now a research scientists with Colorado State University, who envisioned a program that would offer an alternative to the break from classes that universities typically offer students in early spring. Since those initial discussions among the GWS board members, Park Break sessions have been held in eleven different NPS sites across the country. Each session has sponsored six to eight graduate students in various stages off their university programs for a week-long seminar focused on a specific theme relevant to the host park, such as conversation policy and climate change. Sessions have varied in format but all generally have been composed of a week of field and classroom activity with participation from local, state, and national experts.

The George Wright Forum↗
USGS2003

Orbital control of low-latitude seasonality during the Eemian

We used Sr/Ca and stable isotope data from well dated and preserved corals from the northeastern Caribbean to determine the seasonal environmental conditions for four continuous years during the Eemian, the last time the Earth was in a prolonged warm phase. We determined that the seasonal range in SST during the Eemian was 25°–30° C. This is ∼1–2° larger than at present and caused primarily by winter cooling and, only to a small degree, by summer warming. As climate modeling studies indicate, the bias towards colder winters can be explained by changes in low latitude insolation induced by altered orbital parameters, modulated by atmospheric CO 2 levels that were lower than today. Milankovitch forcing at higher latitudes was probably less important.

Geophysical Research Letters↗
USGS2019

Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall

Episodically to continuously active slow-moving landslides are driven by precipitation. Climate change, which is altering both the frequency and magnitude of precipitation world21 wide, is therefore predicted to have a major impact on landslides. Here we examine the behavior of hundreds of slow-moving landslides in northern California in response to large changes in annual precipitation that occurred between 2016 and 2018. We quantify the landslide displacement using repeat-pass radar interferometry and pixel offset tracking techniques on a novel dataset from the airborne NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar. We found that 312 landslides were moving due to extreme rainfall during 2017, compared to 119 during 2016, which was the final year of a historic multi-year drought. However, with a return to below average rainfall in 2018, only 146 landslides remained in motion. The increased number of landslides during 2017 was primarily accommodated by landslides that were smaller than the landslides that remained active between 2016 and 2018. Furthermore, by examining a subset of 51 landslides, we found that 49 had increased velocities during 2017 when compared to 2016. Our results show that slow-moving landslides are sensitive to large changes in annual precipitation, particularly the smaller and thinner landslides that likely experience larger basal pore water pressure changes. Based on climate model predictions for the next century in California, which include increases in annual precipitation and increases in the frequency of dry-to-wet extremes, we hypothesize that there will be an overall increase in landslide activity.

California↗
USGS2022

The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations

Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within-bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near-natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood-generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large-flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming.

Water Resources Research↗
USGS2018

Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS

On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges. In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21 st century with the exception of extreme flows.

California↗
USGS2017

Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data

Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster ( Crassostrea virginica ) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (<25 mm), seed (25–75 mm), and sack (>75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.

Louisiana↗
USGS1973

Ice ages and the thermal equilibrium of the earth

A model for climatic change, and particularly for the changes of the late Cenozoic, involves as its primary variables the albedo of the earth and the heat storage characteristics of the oceans. Geography exerts a strong influence. The model proposed does not require metaphysical causes or astronomical events other than known variations in the earth's orbit.

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