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At least 217 records · Page 12Linked to original sources
USGS2025

An expert elicitation to inform coastal management decision-making for mitigating future hazards

A scientific expert elicitation was conducted to address the feasibility of restoring coastal environments in response to future hazards to best meet management objectives. Subject matter experts produced probabilistic estimates of coastal change metrics used to evaluate decision objectives and alternatives informed by a stakeholder advisory group. Changes in salt marsh extents, storm surge flooding and barrier island morphology by the year 2050 were estimated for three scenarios of management actions (no action, interior headland restoration, beach and dune nourishment), while also considering the effects of future sea level rise (SLR). Collectively the participants were confident in their expectations of increased storm surge flooding with SLR, regardless of management interventions. Estimates of marsh response had large uncertainty, but experts generally hypothesized that marsh area would decrease with increasing SLR if no action was taken, especially in areas already experiencing marsh deterioration. There was agreement that dune heights and barrier island widths would decrease with SLR if no action was taken. Experts felt that beach and dune nourishment may reduce the amount of erosion under future SLR. All experts recognized the dynamic effects of SLR and feedback between bio-geo-physical processes that govern coastal systems. Participants agreed that size and location of management actions were important factors for influencing the coastal response. Expert elicitation is novel in the context of coastal management decision making and can be a useful tool for informing future scientific needs and providing rapid results to end users to inform reallocation of resources surrounding research and application.

Alabama, Mississippi↗
USGS2017

Value of information analysis as a decision support tool for biosecurity

This chapter demonstrates the economic concept of ‘value of information’(VOI), and how biosecurity managers can use VOI analysis to decide whether or not to reduce uncertainty by collecting additional information through monitoring, experimentation, or some other form of research. We first explore how some uncertainties may be scientifically interesting to resolve, but ultimately irrelevant to decision-making. We then develop a prototype model where a manager must choose between eradication or containment of an infestation. Eradication is more cost-effective for smaller infestations, but once the extent reaches a certain size it becomes more cost-effective to contain. When choosing between eradication and containment, how much does knowing the extent of the infestation more exactly improve the outcome of the decision? We calculate the expected value of perfect information (EVPI) about the extent, which provides an upper limit for the value of reducing uncertainty. We then illustrate the approach using the example of red imported fire ant management in south-east Queensland. We calculate the EVPI for three different uncertain variables: the extent of the infestation, the sensitivity (true positive rate) of remote sensing, and the efficacy of baiting.

Book chapter↗
USGS2020

FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes

Inland fishes provide important ecosystem services to communities worldwide and are especially vulnerable to the impacts of climate change. Fish respond to climate change in diverse and nuanced ways, which creates challenges for practitioners of fish conservation, climate change adaptation, and management. Although climate change is known to affect fish globally, a comprehensive online, public database of how climate change has impacted inland fishes worldwide and adaptation or management practices that may address these impacts does not exist. We conducted an extensive, systematic primary literature review to identify peer-reviewed journal publications describing projected and documented examples of climate change impacts on inland fishes. From this standardized Fi sh and Cli mate Change database, FiCli (pronounced fick-lee), researchers and managers can query fish families, species, response types, or geographic locations to obtain summary information on inland fish responses to climate change and recommended management actions. The FiCli database is updatable and provides access to comprehensive published information to inform inland fish conservation and adaptation planning in a changing climate.

Scientific Data↗
USGS2007

Survey of geographical information system and image processing software

The Global Resource Information Database—a part of the United Nations Environment Programme—conducts a bi-annual survey of geographical information system (GIS) and image processing (IP) software. This survey makes information about software products available in developing countries. The 1993 survey showed that the number of installations of GIS, IP, and related software products increased dramatically from 1991 to 1993, mostly in North America and Europe.

International Journal of Remote Sensing↗
USGS2002

Fuzzy logic merger of spectral and ecological information for improved montane forest mapping.

Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA.

Montana↗
USGS2019

The development and delivery of species distribution models to inform decision-making

Information on where species occur is central to conservation and management decisions, but knowledge of distributions can be coarse or incomplete. Species distribution models provide a tool for mapping suitable habitat, and can produce credible, defensible, and repeatable predictive information with which to inform decisions. However, these models are sensitive to data inputs and methodological choices, making it important to assess the reliability and utility of model predictions. We provide a rubric that model developers can use to communicate a model’s attributes and its appropriate uses. We emphasize the importance of tailoring model development and delivery to the species of interest and the intended use, and the advantages of iterative modeling and validation. We highlight how species distribution models have been used to design surveys for new populations, prioritize actions across space, and support regulatory decision-making and compliance, tying these examples back to our rubric.

BioScience↗
USGS2024

Informative priors can account for location uncertainty in stop-level analyses of the North American Breeding Bird Survey (BBS), allowing fine-scale ecological analyses

Ecological inferences are often based on the locations at which species are present, but many species records have substantial uncertainty in spatial metadata, limiting their utility for fine-scale analyses. This is especially prevalent in historical records such as museum specimens, and in some citizen-science data. For example, the North American Breeding Bird Survey (BBS) has 55+ years of bird data from regular transects (“routes”) across the continent but was not designed to capture the spatial component of point count events, limiting analyses of species-habitat relationships for which it would otherwise be well suited. We present a new methodology for quantifying location uncertainty in BBS records using digitized estimated stop locations, deriving the corresponding environmental covariate uncertainty distributions, and incorporating this information into hierarchical species distribution models using informative Bayesian priors. This approach allows for estimation of species–environment relationships in a way that fully accounts for underlying spatial uncertainty. We quantify stop-location uncertainty in BBS data across the central United States, model bird–land cover relationships in the upper Midwest, and validate our method by comparing posterior land cover estimates to known covariate values for a subset of GPS-digitized stop locations. We provide code for implementing this method in R. Posterior land cover estimates (forest, grass/hay, and developed land cover), based on our informative priors, were highly correlated with known land cover values from GPS-digitized stop locations. Our approach thus makes it possible to responsibly leverage large historic and citizen science databases, such as the BBS, for fine-scale ecological analyses.

Ornithological Applications↗
USGS2000

The National Biological Information Infrastructure: Coming of age

Coordinated by the US Geological Survey, the National Biological Information Infrastructure (NBII) is a Web-based system that provides increased access to data and information on the nation's biological resources. The NBII can be viewed from a variety of perspectives. This article - an individual case study and not a broad survey with extensive references to the literature - addresses the structure of the NBII related to thematic sections, infrastructure sections and place-based sections, and other topics such as the Integrated Taxonomic Information System (one of our more innovative tools) and the development of our controlled vocabulary.

Online and CDROM Review↗
USGS2019

Framework for monitoring shrubland community integrity in California Mediterranean type ecosystems: Information for policy makers and land managers

Shrublands in Mediterranean‐type ecosystems worldwide support important ecosystem services including high levels of biodiversity and are threatened by multiple factors in heavily used landscapes. Use, conservation, and management of these landscapes involve diverse stakeholders, making decision processes complex. To be effective, management and land use decisions should be informed by current information on ecosystem quality and resilience. However, obtaining this information is often a challenge due to the extent of landscapes involved. Here we present a conceptual integrity monitoring framework based on simple easily observable ecosystem components readily understood by nonspecialists. Community integrity is defined by plant functional group based on relative proportion of shrubs and nonnative annual grasses. The ability to use these straightforward metrics results from four factors: relatively good alignment of characteristic bird, mammal, and insect communities with shrub cover, positive feedback between annual grasses and short fire intervals, the inhibitory effect of annual grasses on shrub seedling establishment, and similar functional group response to different disturbances. Two additional metrics, indicator species and shrub species diversity, capture subtle yet persistent signatures of disturbance on integrity not reflected in functional group composition. The framework is designed to: categorize habitats into ecosystem integrity classes, forecast likely integrity class changes caused by threats and environmental conditions, and provide a simple reporting mechanism that can be overlain with data on conservation status and vulnerabilities. The proposed framework includes a pilot phase to validate empirical relationships, thresholds, and sampling efficiency. The accessibility of these metrics to nonspecialists is anticipated to enhance communication among stakeholders and thus facilitate problem solving. Leveraging monitoring and mapping programs driven by other needs (e.g., species conservation and fire management) affords meaningful opportunities to offset program costs.

California↗
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↗
USGS2020

Assessment of population genetics and climatic variability can refine climate‐informed seed transfer guidelines

Restoration guidelines increasingly recognize the importance of genetic attributes in translocating native plant materials (NPMs). However, when species‐specific genetic information is unavailable, seed transfer guidelines use climate‐informed seed transfer zones (CSTZs) as an approximation. While CSTZs may improve how NPMs are developed and/or matched to restoration sites, they overlook genetic factors that can diminish restoration success and/or deteriorate natural patterns of genetic diversity and environmental factors that may introduce unexpected variation. Here, we analyze molecular data and geographic patterns of environmental variability across the western United States and demonstrate how they can refine CSTZs. Using genetic data available for 13 relevant plant species, we found that the probability of mixing genetically differentiated individuals (i.e. from different evolutionary lineages, or populations) was approximately 8% when considering locations separated by 50 km and reached nearly 80% by 500 km, which are distances relevant to ecoregionally constrained CSTZs. Furthermore, climate analyses revealed that geographically proximate locations are likely to maintain environmental similarity, regardless of CSTZ or ecoregion assignment. These results suggest constraining CSTZ‐informed seed transfer decisions by distance may mitigate the opportunity for negative genetic outcomes. Furthermore, environmental variability and/or specificity of NPMs (depending upon the restoration strategy) should be achieved by sourcing NPMs from geographically proximate locations to avoid introducing excessive genetic differentiation. Our results highlight the utility of combining molecular genetic data with other genetic inferences (i.e. of adaptation) to determine how best to transfer seed across restoration species' ranges and develop new restoration materials.

Restoration Ecology↗
USGS2024

Advanced quantitative precipitation information: Improving monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay area

Advanced Quantitative Precipitation Information (AQPI) is a synergistic project that combines observations and models to improve monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay Area. As an experimental system, AQPI leverages more than a decade of research, innovation, and implementation of a statewide, state-of-the-art network of observations, and development of the next generation of weather and coastal forecast models. AQPI was developed as a prototype in response to requests from the water management community for improved information on precipitation, riverine, and coastal conditions to inform their decision-making processes. Observation of precipitation in the complex Bay Area landscape of California’s coastal mountain ranges is known to be a challenging problem. But, with new advanced radar network techniques, AQPI is helping fill an important observational gap for this highly populated and vulnerable metropolitan area. The prototype AQPI system consists of improved weather radar data for precipitation estimation; additional surface measurements of precipitation, streamflow, and soil moisture; and a suite of integrated forecast modeling systems to improve situational awareness about current and future water conditions from sky to sea. Together these tools will help improve emergency preparedness and public response to prevent loss of life and destruction of property during extreme storms accompanied by heavy precipitation and high coastal water levels—especially high-moisture laden atmospheric rivers. The Bay Area AQPI system could potentially be replicated in other urban regions in California, the United States, and worldwide.

California↗
USGS2021

Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making

More than 1.6 million Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests were administered daily in the United States at the peak of the epidemic, with a significant focus on individual treatment. Here, we show that objective-driven, strategic sampling designs and analyses can maximize information gain at the population level, which is necessary to increase situational awareness and predict, prepare for, and respond to a pandemic, while also continuing to inform individual treatment. By focusing on specific objectives such as individual treatment or disease prediction and control (e.g., via the collection of population-level statistics to inform lockdown measures or vaccine rollout) and drawing from the literature on capture–recapture methods to deal with nonrandom sampling and testing errors, we illustrate how public health objectives can be achieved even with limited test availability when testing programs are designed a priori to meet those objectives.

PLoS Biology↗
USGS2018

Value of sample information in dynamic, structurally uncertain resource systems

Few if any natural resource systems are completely understood and fully observed. Instead, there almost always is uncertainty about the way a system works and its status at any given time, which can limit effective management. A natural approach to uncertainty is to allocate time and effort to the collection of additional data, on the reasonable assumption that more information will facilitate better understanding and lead to better management. But the collection of more data, either through observation or investigation, requires time and effort that often can be put to other conservation activities. An important question is whether the use of limited resources to improve understanding is justified by the resulting potential for improved management. In this paper we address directly a change in value from new information collected through investigation. We frame the value of information in terms of learning through the management process itself, as well as learning through investigations that are external to the management process but add to our base of understanding. We provide a conceptual framework and metrics for this issue, and illustrate them with examples involving Florida scrub-jays (Aphelocoma coerulescens).

PLoS ONE↗
USGS2019

Do Indigenous American Peoples’ stories inform the study of dog domestication?

I discuss the article “Relationships Between Indigenous American Peoples and Wolves 1: Wolves as Teachers and Guides” (Fogg et al. 2015) and the book “The First Domestication: How Wolves and Humans Coevolved” (Pierotti and Fogg 2017). The article proposed that published stories about interactions between indigenous American peoples and wolves ( Canis lupus ) provide insight into wolf-human relationships as humans began domesticating wolves. In the book, the authors offer a theory of how wolves and humans coevolved by building on the information in the article and the authors’ long experience with captive and pet wolves, wolf-dog hybrids, and dogs. I (1) present arguments and evidence that question the value of indigenous American stories for drawing conclusions about the relationship between early humans and wolves 14,000 yrs BP; (2) demonstrate how indigenous American stories contradict documented information about wolf biology, behavior, and known interactions with humans; and (3) point out important information not considered by the authors about wolf attacks on humans and the importance of rabies in the wolf-human relationship.

Ethnobiological Letters↗
USGS2004

Toward a comprehensive information system to assist invasive species management in Hawaii and Pacific Islands

The need for coordinated regional and global electronic databases to assist prevention, early detection, rapid response, and control of biological invasions is well accepted. The Pacific Basin Information Node (PBIN), a node of the National Biological Information Infrastructure, has been increasingly engaged in the invasive species enterprise since its establishment in 2001. Since this time, PBIN has sought to support frontline efforts at combating invasions, through working with stakeholders in conservation, agriculture, forestry, health, and commerce to support joint information needs. Although initial emphasis has been on Hawaii, cooperative work with other Pacific islands and countries of the Pacific Rim is already underway and planned.

Weed Science↗
USGS2014

Multiple plumage traits convey information about age and within-age-class qualities of a canopy-dwelling songbird, the Cerulean Warbler

Colorful plumage traits in birds may convey multiple, redundant, or unreliable messages about an individual. Plumage may reliably convey information about disparate qualities such as age, condition, and parental ability because discrete tracts of feathers may cause individuals to incur different intrinsic or extrinsic costs. Few studies have examined the information content of plumage in a species that inhabits forest canopies, a habitat with unique light environments and selective pressures. We investigated the information content of four plumage patches (blue-green crown and rump, tail white, and black breast band) in a canopy-dwelling species, the Cerulean Warbler ( Setophaga cerulea ), in relation to age, condition, provisioning, and reproduction. We found that older males displayed wider breast bands, greater tail white, and crown and rump feathers with greater blue-green (435–534 nm) chroma and hue than males in their first potential breeding season. In turn, older birds were in better condition (short and long term) and were reproductively superior to younger birds. We propose that these age-related plumage differences (i.e. delayed plumage maturation) were not a consequence of a life history strategy but instead resulted from constraints during early feather molts. Within age classes, we found evidence to support the multiple messages hypothesis. Birds with greater tail white molted tails in faster, those with more exaggerated rump plumage (lower hue, greater blue-green chroma) provisioned more, and those with lower rump blue-green chroma were in better condition. Despite evidence of reliable signaling in this species, we found no strong relationships between plumage and reproductive performance, potentially because factors other than individual differences more strongly influenced fecundity.

The Auk↗
USGS2018

Monitoring mountains in a changing world: New horizons for the Global Network for Observations and Information on Mountain Environments (GEO-GNOME)

Mountains are globally distributed environments that provide significant societal benefits, a function that is increasingly compromised by climatic change, environmental stress, political and socioeconomic transformations, and unsustainable use of natural resources. Gaps in our understanding of these processes and their interactions limit our capacity to inform decisions, where both generalities of mountain regions (eg climate processes) and specificities (eg context-specific manifestations of climate risks) matter. The Global Network for Observations and Information on Mountain Environments (GEO-GNOME), a Group on Earth Observations initiative, aims to fill these gaps through accessible Earth Observation (EO) as well as in-situ data and information on global change drivers, conditions, and trends. A workshop convened by the Mountain Research Initiative (MRI) revised GEO-GNOME's work plan, galvanizing a network that promotes relevant monitoring of global change in mountains and is responsive to the integrated knowledge needs of policy, research, and management.

Mountain Research and Development↗