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U.S. Geological Survey archived data recovery in Texas, 2008-11

The 2008–11 data rescue and recovery efforts by the U.S. Geological Survey (USGS) Texas Water Science Center resulted in an efficient workflow process, database, and Web user interface for scientists and citizens to access archived environmental information with practical applications. Much of this information is unique and has never been readily available to the public. The methods developed and lessons learned during this effort are now being applied to facilitate recovering archived information requested by USGS scientists, cooperators, and the general public.

Texas↗

Adapting to climate change at Olympic National Forest and Olympic National Park

Climate change presents a major challenge to natural resource managers both because of the magnitude of potential effects of climate change on ecosystem structure, processes, and function, and because of the uncertainty associated with those potential ecological effects. Concrete ways to adapt to climate change are needed to help natural resource managers take the first steps to incorporate climate change into management and take advantage of opportunities to counteract the negative effects of climate change. We began a climate change adaptation case study at Olympic National Forest (ONF) in partnership with Olympic National Park (ONP) to determine how to adapt management of federal lands on the Olympic Peninsula, Washington, to climate change. The case study began in the summer of 2008 and continued for 1½ years. The case study process involved science-based sensitivity assessments, review of management activities and constraints, and adaptation workshops in each of four focus areas (hydrology and roads, fish, vegetation, and wildlife). The process produced adaptation options for ONF and ONP, and illustrated the utility of place-based vulnerability assessment and science-management workshops in adapting to climate change. The case study process provides an example for other national forests, national parks, and natural resource agencies of how federal land management units can collaborate in the initial stages of climate change adaptation. Many of the ideas generated through this process can potentially be applied in other locations and in other agencies

Washington↗

IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the education community (IUPAC Technical Report)

The IUPAC (International Union of Pure and Applied Chemistry) Periodic Table of the Elements and Isotopes (IPTEI) was created to familiarize students, teachers, and non-professionals with the existence and importance of isotopes of the chemical elements. The IPTEI is modeled on the familiar Periodic Table of the Chemical Elements. The IPTEI is intended to hang on the walls of chemistry laboratories and classrooms. Each cell of the IPTEI provides the chemical name, symbol, atomic number, and standard atomic weight of an element. Color-coded pie charts in each element cell display the stable isotopes and the relatively long lived radioactive isotopes having characteristic terrestrial isotopic compositions that determine the standard atomic weight of each element. The background color scheme of cells categorizes the 118 elements into four groups: (1) white indicates the element has no standard atomic weight, (2) blue indicates the element has only one isotope that is used to determine its standard atomic weight, which is given as a single value with an uncertainty, (3) yellow indicates the element has two or more isotopes that are used to determine its standard atomic weight, which is given as a single value with an uncertainty, and (4) pink indicates the element has a well-documented variation in its atomic weight, and the standard atomic weight is expressed as an interval. An element-by-element review accompanies the IPTEI and includes a chart of all known stable and radioactive isotopes for each element. Practical applications of isotopic measurements and technologies are included for the following fields: forensic science, geochronology, Earth-system sciences, environmental science, and human health sciences, including medical diagnosis and treatment.

Pure and Applied Chemistry↗

Phase 1 studies summary of major findings of the South Bay Salt Pond Restoration Project, South San Francisco Bay, California

Executive Summary The South Bay Salt Pond Restoration Project (Project) is one of the largest restoration efforts in the United States. It is located in South San Francisco Bay of California. It is unique not only for its size—more than 15,000 acres—but also for its location adjacent to one of the nation’s largest urban areas, home to more than 4 million people (Alameda, Santa Clara, and San Mateo Counties). The Project is intended to restore and enhance wetlands in South San Francisco Bay while providing for flood management, wildlife-oriented public access, and recreation. Restoration goals of the project are to provide a mosaic of saltmarsh habitat to benefit marsh species and managed ponds to benefit waterbirds, throughout 3 complexes and 54 former salt ponds. Although much is known about the project area, significant uncertainties remain with a project of this geographic and temporal scale of an estimated 50 years to complete the restoration. For example, in order to convert anywhere from 50 to 90 percent of the existing managed ponds to saltmarsh habitat, conservation managers first enhance the habitat of managed ponds in order to increase use by waterbirds, and provide migratory, wintering, and nesting habitat for more than 90 species of waterbirds. Project managers have concluded that the best way to address these uncertainties is to carefully implement the project in phases and learn from the outcome of each phase. The Adaptive Management Plan (AMP) identifies specific restoration targets for multiple aspects of the Project and defines triggers that would necessitate some type of management action if a particular aspect is trending negatively. U.S. Geological Survey (USGS) biologist Laura Valoppi served as the project Lead Scientist and oversaw implementation of the AMP in coordination with other members of the Project Management Team (PMT), comprised of representatives from the California State Coastal Conservancy, California Department of Fish and Wildlife, the Santa Clara Valley Water District, the U.S. Army Corps of Engineers, and the U.S. Fish and Wildlife Service. To implement the AMP, the PMT have selected and funded applied studies and monitoring projects to address key uncertainties. This information is used by the PMT to make decisions about current management of the project area and future restoration actions in order to meet project. This document summarizes the major scientific findings from studies conducted from 2009 to 2016, as part of the science program that was conducted in conjunction with Phase 1 restoration and management actions. Additionally, this report summarizes the management response to the study results under the guidance of the AMP framework and provides a list of suggested studies to be conducted in “Phase 2–A scorecard summarizing the Project’s progress toward meeting the AMP goals for a range of Project objectives.” The scoring to date indicates that the Project is meeting or exceeding expectations for sediment accretion and western snowy plover ( Charadrius alexandrinus nivosus ) recovery. There is uncertainty with respect to objectives for California gulls ( Larus californicus ), California least tern ( Sternula antillarum ), steelhead trout ( Oncorhynchus mykiss ), and regulatory water quality objectives. Water quality and algal blooms, specifically of the managed ponds, is indicated as trending negative. However, the vast majority of objectives are trending positive, including increased abundance for a number of bird guilds, increasing marsh habitat, maintenance of mudflats, visitor experience, estuarine fish numbers, and special-status marsh species numbers.

California↗

Can arsenic occurrence rate in bedrock aquifers be predicted?

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 μg L –1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 μg L –1 ) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.

Environmental Science & Technology↗

Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations

Quantitative understanding of Congo River basin hydrological behavior is poor because of the basin’s limited hydrometeorological observation network. In cases such as the Congo basin where ground data are scarce, satellite-based estimates of rainfall, such as those from the joint NASA/JAXA Tropical Rainfall Measuring Mission (TRMM), can be used to quantify rainfall patterns. This study tests and reports the use of limited rainfall gauge data within the Democratic Republic of Congo (DRC) to recalibrate a TRMM science product (TRMM 3B42, version 6) in characterizing precipitation and climate in the Congo basin. Rainfall estimates from TRMM 3B42, version 6, are compared and adjusted using ground precipitation data from 12 DRC meteorological stations from 1998 to 2007. Adjustment is achieved on a monthly scale by using a regression-tree algorithm. The output is a new, basin-specific estimate of monthly and annual rainfall and climate types across the Congo basin. This new product and the latest version-7 TRMM 3B43 science product are validated by using an independent long-term dataset of historical isohyets. Standard errors of the estimate, root-mean-square errors, and regression coefficients r were slightly and uniformly better with the recalibration from this study when compared with the 3B43 product (mean monthly standard errors of 31 and 40 mm of precipitation and mean r 2 of 0.85 and 0.82, respectively), but the 3B43 product was slightly better in terms of bias estimation (1.02 and 1.00). Despite reasonable doubts that have been expressed in studies of other tropical regions, within the Congo basin the TRMM science product (3B43) performed in a manner that is comparable to the performance of the recalibrated product that is described in this study.

Journal of Applied Meteorology and Climatology↗

Estimating national water use associated with unconventional oil and gas development

The U.S. Geological Survey’s (USGS) Water Availability and Use Science Program (WAUSP) goals are to provide a more accurate assessment of the status of the water resources of the United States and assist in the determination of the quantity and quality of water that is available for beneficial uses. These assessments would identify long-term trends or changes in water availability since the 1950s in the United States and help to develop the basis for an improved ability to forecast water avail- ability for future economic, energy-production, and environmental uses. The National Water Census ( http://water.usgs.gov/watercensus/ ), a research program of the WAUSP, supports studies to develop new water accounting tools and assess water availability at the regional and national scales. Studies supported by this program target focus areas with identified water availability concerns and topical science themes related to the use of water within a specific type of environmental setting. The topical study described in this fact sheet will focus on understanding the relation between production of unconventional oil and gas (UOG) for energy and the water needed to produce and sustain this type of energy development. This relation applies to the life-cycle of renewable and nonrenewable forms of UOG energy and includes extraction, production, refinement, delivery, and disposal of waste byproducts. Water-use data and models derived from this topical study will be applied to other similar oil and gas plays within the United States to help resource managers assess and account for water used or needed in these areas. Additionally, the results from this topical study will be used to further refine the methods used in compiling water-use data for selected categories (for example, mining, domestic self-supplied, public supply, and wastewater) in the USGS’s 5-year national water-use estimates reports ( http://water.usgs.gov/watuse/ ).

Fact Sheet↗

Temporal and spatial variations in fly ash quality

Fly ash quality, both as the amount of petrographically distinguishable carbons and in chemistry, varies in both time and space. Temporal variations are a function of a number of variables. Variables can include variations in the coal blend organic petrography, mineralogy, and chemistry; variations in the pulverization of the coal, both as a function of the coal's Hardgrove grindability index and as a function of the maintenance and settings of the pulverizers; and variations in the operating conditions of the boiler, including changes in the pollution control system. Spatial variation, as an instantaneous measure of fly ash characteristics, should not involve changes in the first two sets of variables listed above. Spatial variations are a function of the gas flow within the boiler and ducts, certain flow conditions leading to a tendency for segregation of the less-dense carbons in one portion of the gas stream. Caution must be applied in sampling fly ash. Samples from a single bin, or series of bins, m ay not be representative of the whole fly ash, providing a biased view of the nature of the material. Further, it is generally not possible to be certain about variation until the analysis of the ash is complete. ?? 2001 Elsevier Science B.V. All rights reserved.

Fuel Processing Technology↗

An approach for decomposing river water-quality trends into different flow classes

A number of statistical approaches have been developed to quantify the overall trend in river water quality, but most approaches are not intended for reporting separate trends for different flow conditions. We propose an approach called FN 2Q , which is an extension of the flow-normalization (FN) procedure of the well-established WRTDS (“Weighted Regressions on Time, Discharge, and Season”) method. The FN 2Q approach provides a daily time series of low-flow and high-flow FN flux estimates that represent the lower and upper half of daily riverflow observations that occurred on each calendar day across the period of record. These daily estimates can be summarized into any time period of interest (e.g., monthly, seasonal, or annual) for quantifying trends. The proposed approach is illustrated with an application to a record of total nitrogen concentration (632 samples) collected between 1985 and 2018 from the South Fork Shenandoah River at Front Royal, Virginia (USA). Results show that the overall FN flux of total nitrogen has declined in the period of 1985–2018, which is mainly attributable to FN flux decline in the low-flow class. Furthermore, the decline in the low-flow class was highly correlated with wastewater effluent loads, indicating that the upgrades of treatment technology at wastewater treatment facilities have likely led to water-quality improvement under low-flow conditions. The high-flow FN flux showed a spike around 2007, which was likely caused by increased delivery of particulate nitrogen associated with sediment transport. The case study demonstrates the utility of the FN 2Q approach toward not only characterizing the changes in river water quality but also guiding the direction of additional analysis for capturing the underlying drivers. The FN 2Q approach (and the published code) can easily be applied to widely available river monitoring records to quantify water-quality trends under different flow conditions to enhance understanding of river water-quality dynamics.

Virginia↗

Using linear models with correlated errors to analyze changes in abundance of Lake Michigan fishes: 1973-1992

We examined annual changes in relative abundance of Lake Michigan fishes using linear models with correlated errors in space and time. Abundance of bloater ( Coregonus hoyi ), deepwater sculpin ( Myoxocephalus thompsoni ), slimy sculpin ( Cottus cognatus ), alewife ( Alosa pseudoharengus ), and rainbow smelt ( Osmerus mordax ) was monitored with bottom trawls at 10 discrete depths (between 18 and 110 m) off eight fixed ports from 1973 to 1992. The model describing abundance included fixed effects of year, port, depth, and interaction terms as well as quadratic and cubic effects of year and depth because changes in abundance were not strictly linear. Observed temporal trends in abundance varied with species and depth. Additionally, trends in alewife and slimy sculpin abundances depended on port. Cubic trends in the abundance of bloater and quadratic trends in deepwater sculpin and rainbow smelt abundances were similar among ports, permitting lakewide inferences for these species. Mean bloater abundance was low throughout the 1970s, increased during the 1980s, and reached high levels by 1990. Mean abundances of deepwater sculpin and rainbow smelt increased from 1973 to the mid-1980s and declined thereafter. The linear model with correlated errors can be readily applied to repeated-measures data from other fixed-station fishery surveys and is appropriate for data exhibiting spatial and temporal autocorrelations.

Canadian Journal of Fisheries and Aquatic Sciences↗

Multi-scale responses of vegetation to removal of horse grazing from Great Basin (USA) mountain ranges

Although free-roaming equids occur on all of the world's continents except Antarctica, very few studies (and none in the Great Basin, USA) have either investigated their grazing effects on vegetation at more than one spatial scale or compared characteristics of areas from which grazing has been removed to those of currently grazed areas. We compared characteristics of vegetation at 19 sites in nine mountain ranges of the western Great Basin; sites were either grazed by feral horses (Equus caballus) or had had horses removed for the last 10-14 years. We selected horse-occupied and horse-removed sites with similar aspect, slope, fire history, grazing pressure by cattle (minimal to none), and dominant vegetation (Artemisia tridentata). During 1997 and 1998, line-intercept transects randomly located within sites revealed that horse-removed sites exhibited 1.1-1.9 times greater shrub cover, 1.2-1.5 times greater total plant cover, 2-12 species greater plant species richness, and 1.9-2.9 times greater cover and 1.1-2.4 times greater frequency of native grasses than did horse-occupied sites. In contrast, sites with horses tended to have more grazing-resistant forbs and exotic plants. Direction and magnitude of landscape-scale results were corroborated by smaller-scale comparisons within horse-occupied sites of horse-trail transects and (randomly located) transects that characterized overall site conditions. Information-theoretic analyses that incorporated various subsets of abiotic variables suggested that presence of horses was generally a strong determinant of those vegetation-related variables that differed significantly between treatments, especially frequency and cover of grasses, but also species richness and shrub cover and frequency. In contrast, abiotic variables such as precipitation, site elevation, and soil erodibility best predicted characteristics such as forb cover, shrub frequency, and continuity of the shrub canopy. We found species richness of plants monotonically decreased across sites as grazing disturbance increased, suggesting that either the bell-shaped diversity-disturbance curve of the intermediate-disturbance hypothesis does not apply in this system or that most sites are already all on the greater-disturbance slope of the curve. In our study, numerous vegetation properties of less-grazed areas and sites differed notably from horse-grazed sites at local and landscape scales during a wetter and an average-precipitation year. ?? 2007 Springer Science+Business Media B.V.

Plant Ecology↗

A review and synthesis of recreation ecology research supporting carrying capacity and visitor use management decisionmaking

Resource and experiential impacts associated with visitation to wilderness and other similar backcountry settings have long been addressed by land managers under the context of “carrying capacity” decisionmaking. Determining a maximum level of allowable use, below which high-quality resource and experiential conditions would be sustained, was an early focus in the 1960s and 1970s. However, decades of recreation ecology research have shown that the severity and areal extent of visitor impact problems are influenced by an interrelated array of use-related, environmental, and managerial factors. This complexity, with similar findings from social science research, prompted scientists and managers to develop more comprehensive carrying capacity frameworks, including a new Visitor Use Management framework. These frameworks rely on a diverse array of management strategies and actions, often termed a “management toolbox,” for resolving visitor impact problems. This article reviews the most recent and relevant recreation ecology studies that have been applied in wildland settings to avoid or minimize resource impacts. The key findings and their management implications are highlighted to support the professional management of common trail, recreation site, and wildlife impact problems. These studies illustrate the need to select from a more diverse array of impact management strategies and actions based on an evaluation of problems to identify the most influential factors that can be manipulated.

Journal of Forestry↗

Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

Book↗

The future of recreational fisheries: Advances in science, monitoring, management, and practice

Recreational fisheries (RF) are complex social-ecological systems that play an important role in aquatic environments while generating significant social and economic benefits around the world. The nature of RF is diverse and rapidly evolving, including the participants, their priorities and behaviors, and the related ecological impacts and social and economic benefits. RF can lead to negative ecological impacts, particularly through overexploitation of fish populations and spread of non-native species and genotypes through stocking. Hence, careful management and monitoring of RF is essential to sustain these ecologically and socioeconomically important resources. This special issue on recreational fisheries contains diverse research, syntheses, and perspectives that highlight the advances being made in RF research, monitoring, management, and practice, which we summarize here. Co-management actions are rising, often involving diverse interest groups including government and non-government organizations; applying collaborative management practices can help balance social and economic benefits with conservation targets. Technological and methodological advances are improving the ability to monitor biological, social, and economic dynamics of RF, which underpin the ability to maximize RF benefits through management actions. To ensure RF sustainability, much research focuses on the ecological aspects of RF, as well as the development of management and angling practices that reduce negative impacts on fish populations. For example, angler behavior can be influenced to conform to conservation-minded angling practices through regulations, but is often best accomplished through growing bottom-up social change movements. Anglers can also play an important role in fisheries monitoring and conservation, including providing data on fish abundance and assemblages (i.e., citizen science). The increasing impacts that growing human populations are having on the global environment are threatening many of the natural resources and ecosystem services they provide, including valuable RF. However, with careful development of research initiatives, monitoring and management, sustainable RF can generate positive outcomes for both society and natural ecosystems and help solve allocation conflicts with commercial fisheries and conservation.

Fisheries Research↗

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗

Understanding how microbiomes influence the systems they inhabit

Translating the ever-increasing wealth of information on microbiomes (environment, host, or built environment) to advance the understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties, and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system level processes they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted from constituent taxa (community aggregated traits) from and those properties that are currently unable to be predicted from constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these categories and connect these three categories of microbial characteristics with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.

Nature Microbiology↗

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Proceedings of the National Academy of Sciences of↗

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↗