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USGS2023

Models for linking hunter retention and recruitment to regulations and game populations

Introduction: Declining hunter populations across North America present wildlife management agencies with the prospect of declining revenues for wildlife conservation and management and the need for new tools to evaluate management strategies and predict future status of game species and hunters. Methods: Here we present a modeling framework and potential decision support tool for managers to link future hunter population dynamics to regulatory restrictiveness, prey abundance, and harvest success. Our hunter model is parameterized based on the authors’ judgment and can be used for demonstration purposes. We simulated three scenarios of restricted harvest, moderate harvest and liberal harvest. Results: Our simulations show that even though liberal harvest predicts higher cumulative license sales revenue, it corresponds with a slight decline in buck abundance over 10 years. In contrast, highly restrictive harvest corresponds with deer population growth, but a near collapse of hunter populations. Our model demonstrates that managers might face tradeoffs between managing for deer population abundance and hunting revenue and clarifies how these factors might affect decision making. Discussion: The utility of our tool would be dependent on accessing data on hunter retention and recruitment, however, the strength of our paper is in highlighting a new way of thinking about and potentially addressing these potential tradeoffs. Further, these simulations demonstrate that these tools could be used to evaluate management strategies but also highlight uncertainties, establish research priorities, and potentially design an adaptive management framework.

Alabama↗

USGS2020

Deep-sea coral and sponge taxa increase demersal fish diversity and the probability of fish presence

Fishes are known to use deep-sea coral and sponge (DSCS) species as habitat, but it is uncertain whether this relationship is facultative (circumstantial and not restricted to a particular function) or obligate (necessary to sustain fish populations). To explore whether DSCS provide essential habitats for demersal fishes, we analyzed 10 years of submersible survey video transect data, documenting the locations and abundance of DSCS and demersal fishes in the Southern California Bight (SCB). We first classified the different habitats in which fishes and DSCS taxa occurred using cluster analysis, which revealed four distinct DSCS assemblages based on depth and substratum. We then used logistic regression and gradient forest analysis to identify the ecological correlates most associated with the presence of rockfish taxa ( Sebastes spp.) and biodiversity. After accounting for spatial autocorrelation, the factors most related to the presence of rockfishes were depth, coral height, and the abundance of a few key DSCS taxa. Of particular interest, we found that young-of-the-year rockfishes were more likely to be present in locations with taller coral and increased densities of Plumarella longispina , Lophelia pertusa , and two sponge taxa. This suggests these DSCS taxa may serve as important rearing habitat for rockfishes. Similarly, the gradient forest analysis found the most important ecological correlates for fish biodiversity were depth, coral cover, coral height, and a subset of DSCS taxa. Of the 10 top-ranked DSCS taxa in the gradient forest (out of 39 potential DSCS taxa), 6 also were associated with increased probability of fish presence in the logistic regression. The weight of evidence from these multiple analytical methods suggests that this subset of DSCS taxa are important fish habitats. In this paper we describe methods to characterize demersal communities and highlight which DSCS taxa provide habitat to demersal fishes, which is valuable information to fisheries agencies tasked to manage these fishes and their essential habitats.

California↗

USGS2026

The surface elevation table and marker horizon technique: A protocol for measuring wetland elevation dynamics, narrative (Version 2.0)

The National Park Service (NPS), in response to the growing evidence and awareness of the effects of climate change on federal lands, determined that monitoring wetland elevation change is a top priority in North Atlantic Coastal parks (Stevens et al. 2010). As a result, the NPS Northeast Coastal and Barrier Network (NCBN) in collaboration with colleagues from the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA) have developed a protocol for monitoring wetland elevation change and other processes important for determining the viability of wetland communities. Although focused on North Atlantic Coastal parks, this document is applicable to all coastal and inland wetland regions. Wetlands exist within a narrow range of elevation that is influenced by local hydrologic conditions. For tidally influenced coastal wetlands, local hydrologic conditions may be changing as sea levels continue to rise. As sea level rises, coastal wetland systems may either a) build elevation to maintain favorable hydrologic conditions for their survival or b) become increasingly inundated beyond their physiological tolerance resulting in an eventual conversion to open water. A better understanding of these processes will help to determine the present and future viability of coastal wetlands managed by the NPS and can help address measures to ensure these communities exist into the future. This protocol provides the reader with instructions and guidelines on designing a monitoring plan or study to: Quantify elevation change in wetlands with the Surface Elevation Table (SET); understand the processes that influence elevation change, including vertical accretion (SET and Marker Horizon methods); survey the wetland surface and SET mark to a common reference datum to allow for comparing sample stations to each other and to local tidal datums; survey the SET mark to monitor its relative stability; and establish water level equipment to characterize the hydrology and tidal datums for a particular wetland site or sites. The protocol is divided into two documents: The narrative (this document) presents an overview of all aspects of monitoring wetland elevation dynamics, and a document of Standard Operating Procedures (SOPs) with detailed instructions on the design, installation, data collection, and data management in support of monitoring changes in wetland elevation.

Science Report↗

USGS2009

Evaluation of strobe lights to reduce turbine entrainment of juvenile steelhead ( Oncorhynchus mykiss ) at Cowlitz Falls Dam, Washington

We conducted a radiotelemetry evaluation to determine if strobe lights could be used to decrease turbine entrainment of juvenile steelhead ( Oncorhynchus mykiss ) at Cowlitz Falls Dam, Washington. We found that radio-tagged juvenile steelhead approached and entered two spillbays (one lighted, one unlighted) in equal proportions. However, the presence of strobe lights was associated with decreased spillbay residence time of juvenile steelhead and increased passage through induction slots (secondary turbine intakes located upstream of the ogee on the spillway). Mean residence time of tagged fish inside the lighted spillbay was 14 min compared to 62 min inside the unlighted spillbay. Radio-tagged steelhead passed through induction slots at a higher proportion in the lighted spillbay (55%) than in the unlighted spillbay (26%). Recent studies have suggested that strobe lights can induce torpor in juvenile salmonids. We believe that strobe light exposure affected fish in our study at a location where they were susceptible to high flows thereby reducing mean residence time and increasing the proportion of tagged fish entering induction slots in the lighted spillbay. Our results suggest that factors such as deployment location, exposure, and flow are important variables that should be considered when evaluating strobe lights as a potential fish-deterring management tool.

Northwest Science↗

USGS2015

On a report that the 2012 M 6.0 earthquake in Italy was predicted after seeing an unusual cloud formation

Several recently published reports have suggested that semi-stationary linear-cloud formations might be causally precursory to earthquakes. We examine the report of Guangmeng and Jie (2013), who claim to have predicted the 2012 M 6.0 earthquake in the Po Valley of northern Italy after seeing a satellite photograph (a digital image) showing a linear-cloud formation over the eastern Apennine Mountains of central Italy. From inspection of 4 years of satellite images we find numerous examples of linear-cloud formations over Italy. A simple test shows no obvious statistical relationship between the occurrence of these cloud formations and earthquakes that occurred in and around Italy. All of the linear-cloud formations we have identified in satellite images, including that which Guangmeng and Jie (2013) claim to have used to predict the 2012 earthquake, appear to be orographic – formed by the interaction of moisture-laden wind flowing over mountains. Guangmeng and Jie (2013) have not clearly stated how linear-cloud formations can be used to predict the size, location, and time of an earthquake, and they have not published an account of all of their predictions (including any unsuccessful predictions). We are skeptical of the validity of the claim by Guangmeng and Jie (2013) that they have managed to predict any earthquakes.

Natural Hazards and Earth System Sciences↗

USGS2015

Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes: Implications for flooding and drought

We evaluated the spatial and seasonal responses of precipitation in the Ganges and Brahmaputra basins as modulated by the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modes using Global Precipitation Climatology Centre (GPCC) full data reanalysis of monthly global land-surface precipitation data from 1901 to 2010 with a spatial resolution of 0.5° × 0.5°. The GPCC monthly total precipitation climatology targeting the period 1951–2000 was used to compute gridded monthly anomalies for the entire time period. The gridded monthly anomalies were averaged for the years influenced by combinations of climate modes. Occurrences of El Niño alone significantly reduce (88% of the long-term average (LTA)) precipitation during the monsoon months in the western and southeastern Ganges Basin. In contrast, occurrences of La Niña and co-occurrences of La Niña and negative IOD events significantly enhance (110 and 109% of LTA in the Ganges and Brahmaputra Basin, respectively) precipitation across both basins. When El Niño co-occurs with positive IOD events, the impacts of El Niño on the basins' precipitation diminishes. When there is no active ENSO or IOD events (occurring in 41 out of 110 years), precipitation remains below average (95% of LTA) in the agriculturally intensive areas of Haryana, Uttar Pradesh, Rajasthan, Madhya Pradesh, and Western Nepal in the Ganges Basin, whereas precipitation remains average to above average (104% of LTA) across the Brahmaputra Basin. This pattern implies that a regular water deficit is likely, especially in the Ganges Basin, with implications for the agriculture sector due to its reliance on consistent rainfall for successful production. Historically, major droughts occurred during El Niño and co-occurrences of El Niño and positive IOD events, while major flooding occurred during La Niña and co-occurrences of La Niña and negative IOD events in the basins. This observational analysis will facilitate well-informed decision making in minimizing natural hazard risks and climate impacts on agriculture, and supports development of strategies ensuring optimized use of water resources in best management practice under a changing climate.

Brahmaputra Basin, Ganges Basin↗

USGS2021

Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico

Landslides are frequent and damaging natural hazards that threaten the people and the natural and built environments of Puerto Rico. In 2017, more than 70,000 landslides were triggered across the island by heavy rainfall from Hurricane María, prompting requests by local professionals for landslide education and outreach materials. This article describes a novel collaborative risk communication framework that was developed to meet those requests and shaped the creation of a Spanish- and English-language Landslide Guide for Residents of Puerto Rico. Collaborative risk communication is defined here as an iterative process guided by a set of principles for the interdisciplinary coproduction of hazards information and communication products by local and external stakeholders. The process that supports this form of risk communication involves mapping out the risk communication stakeholders in the at-risk or disaster-affected location—in this case Puerto Rico—and collaborating over time to address a shared challenge, such as landslide hazards. The approach described in this article involved the formation of a core team of government and university partners that expanded in membership to conduct collaborative work with an informal network of hazards professionals from diverse sectors in Puerto Rico. The following principles guided this process: cultural competence, ethical engagement, listening, inclusive decision making, empathy, convergence research, nested mentoring, adaptability, and reciprocity. This article contributes to the field of risk communication and emergency management by detailing these principles and the associated process in order to motivate collaborative risk communication efforts in different geographic and cultural contexts. While the work described here focuses on addressing landslides, the principles and process are transferable to other natural, technological, and willful human-caused hazards. They may also serve as a roadmap for future partnerships among government agencies and university researchers to inform the cocreation of science education and outreach tools.

Puerto Rico↗

USGS2011

Proceedings of the third USGS modeling conference, June 7-11, 2010, Broomfield, Colorado-Understanding and predicting for a changing world

The Third USGS Modeling Conference was held June 7th-11, 2010, in Broomfield, Colorado. The conference focused on the development and application of analytical and theoretical models and data availability that support managing the Nation's resources and help protect lives and property. Participants at the conference included scientists and managers from Department of the Interior (DOI) Bureaus; national and international Federal, State, and local agencies; academic institutions; and nongovernmental organizations. The conference was organized according to DOI priorities and the strategic directions of the USGS Science Strategy; the following themes were emphasized: (1) Understanding Ecosystems and Restoring America's Treasured Landscapes; (2) Climate Change and Impact; (3) New Energy Frontier and Minerals for America; (4) A National Hazards, Risk, and Resilience Assessment Program; (5) Role of Environment and Wildlife in Human Health; (6) A Water Census of the United States; and (7) New Methods of Investigation and Discovery. The conference theme-"Understanding and Predicting for a Changing World"-focused on the following goals: advance development and application of models; provide tools that address management issues; present state-of-the-art models ranging from individual phenomena to integrated systems; and foster a working community among scientists and managers.

Scientific Investigations Report↗

USGS1995

Journal news

Statistical power (and conversely, Type II error) is often ignored by biologists. Power is important to consider in the design of studies, to ensure that sufficient resources are allocated to address a hypothesis under examination. Deter- mining appropriate sample size when designing experiments or calculating power for a statistical test requires an investigator to consider the importance of making incorrect conclusions about the experimental hypothesis and the biological importance of the alternative hypothesis (or the biological effect size researchers are attempting to measure). Poorly designed studies frequently provide results that are at best equivocal, and do little to advance science or assist in decision making. Completed studies that fail to reject Ho should consider power and the related probability of a Type II error in the interpretation of results, particularly when implicit or explicit acceptance of Ho is used to support a biological hypothesis or management decision. Investigators must consider the biological question they wish to answer (Tacha et al. 1982) and assess power on the basis of biologically significant differences (Taylor and Gerrodette 1993). Power calculations are somewhat subjective, because the author must specify either f or the minimum difference that is biologically important. Biologists may have different ideas about what values are appropriate. While determining biological significance is of central importance in power analysis, it is also an issue of importance in wildlife science. Procedures, references, and computer software to compute power are accessible; therefore, authors should consider power. We welcome comments or suggestions on this subject.

Journal of Wildlife Management↗

USGS2017

Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

The distribution and abundance of pinyon ( Pinus monophylla ) and juniper ( Juniperus osteosperma, J. occidentalis ) trees (hereinafter, "pinyon-juniper") in sagebrush ( Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes . Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst ™ . This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC , including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

California, Nevada↗

USGS2023

A watershed moment for western U.S. dams

The summer of 2023 is a notable time for water-resource management in the western United States: Glen Canyon Dam, on the Colorado River, turns 60 years old while the largest dam-removal project in history is beginning on the Klamath River. This commentary discusses these events in the context of a changing paradigm for dam and reservoir management in this region. Since the era of large dam building began to wane six decades ago, new challenges have arisen for dam and reservoir management owing to climate change, population increase, reservoir sedimentation, declining safety of aging dams, and more environmentally focused management objectives. Today we also better understand dams' benefits, costs, and environmental impacts, including some that were unforeseen and took decades to become apparent. Where dams have become unsafe, obsolete (e.g., due to excessive reservoir sedimentation), and uneconomical beyond saving, dam removal has become common. The science and practice of dam removal are accelerating rapidly, and some long-term physical and biological response studies are now available. Removal of four hydroelectric dams on the Klamath River will be a larger and more complex project than any previous dam removal. The imminency of this project reflects a very different situation for dam and reservoir management than 60 years ago. Looking forward, dam and reservoir management in the western United States and worldwide will require continued collaboration and innovative thinking to meet a wide range of objectives and to manage water resources sustainably for future generations.

Water Resources Research↗

USGS2022

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle ( Glyptemys insculpta ) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λ mean = 0.952, 95% CI: 0.87–1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

Journal of Environmental Management↗

USGS2024

State of the data: Assessing the FAIRness of USGS data

In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.

Data Science Journal↗

USGS2017

Estimating occupancy probability of moose using hunter survey data

Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose ( Alces alces ) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer ( Odocoileus virginianus ) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.

New York↗

USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗

USGS2016

Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts

Temperate grasslands have suffered disproportionally from conversion to cropland, degradation and fragmentation. A large proportion of the world’s remaining near-natural grassland is situated in Kazakhstan. We aimed to assess current and emerging threats to steppe and semi-desert biodiversity in Kazakhstan and evaluate conservation research priorities. We conducted a horizon-scanning exercise among conservationists from academia and practice. We first compiled a list of 45 potential threats. These were then ranked by the survey participants according to their perceived severity, the need for research on them, and their novelty. The highest-ranked threats were related to changes in land use (leading to habitat loss and deterioration), direct persecution of wildlife, and rapid infrastructure development due to economic and population growth. Research needs were identified largely in the same areas, and the mean scores of threat severity and research need were highly correlated. Novel threats comprised habitat loss by photovoltaic and wind power stations, climate change and changes in agriculture such as the introduction of biofuels. However, novelty was not correlated with threat severity or research priority, suggesting that the most severe threats are the established ones. Important goals towards more effective steppe and semi-desert conservation in Kazakhstan include more cross-sector collaboration (e.g. by involving stakeholders in conservation and agriculture), greater allocation of funds to under-staffed areas (e.g. protected area management), better representativeness and complementarity in the protected area system and enhanced data collection for wildlife monitoring and threat assessments (including the use of citizen-science databases).

Biodiversity and Conservation↗

USGS2010

Challenges in merging fisheries research and management: The Upper Mississippi River experience

The Upper Mississippi River System (UMRS) is a geographically diverse basin extending 10?? north temperate latitude that has produced fishes for humans for millennia. During European colonization through the present, the UMRS has been modified to meet multiple demands such as navigation and flood control. Invasive species, notably the common carp, have dominated fisheries in both positive and negative ways. Through time, environmental decline plus reduced economic incentives have degraded opportunities for fishery production. A renewed focus on fisheries in the UMRS may be dawning. Commercial harvest and corresponding economic value of native and non-native species along the river corridor fluctuates but appears to be increasing. Recreational use will depend on access and societal perceptions of the river. Interactions (e. g., disease and invasive species transmission) among fish assemblages within the UMRS, the Great Lakes, and other lakes and rivers are rising. Data collection for fisheries has varied in intensity and contiguousness through time, although resources for research and management may be growing. As fisheries production likely relies on the interconnectivity of fish populations and associated ecosystem processes among river reaches (e. g., between the pooled and unpooled UMRS), species-level processes such as genetics, life-history interactions, and migratory behavior need to be placed in the context of broad ecosystem- and landscape-scale restoration. Formal communication among a diverse group of researchers, managers, and public stakeholders crossing geographic and disciplinary boundaries is necessary through peer-reviewed publications, moderated interactions, and the embrace of emerging information technologies. ?? Springer Science+Business Media B.V. 2010.

Hydrobiologia↗

USGS2009

LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment

LANDFIRE is a 5-year, multipartner project producing consistent and comprehensive maps and data describing vegetation, wildland fuel, fire regimes and ecological departure from historical conditions across the United States. It is a shared project between the wildland fire management and research and development programs of the US Department of Agriculture Forest Service and US Department of the Interior. LANDFIRE meets agency and partner needs for comprehensive, integrated data to support landscape-level fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. The LANDFIRE data production framework is interdisciplinary, science-based and fully repeatable, and integrates many geospatial technologies including biophysical gradient analyses, remote sensing, vegetation modelling, ecological simulation, and landscape disturbance and successional modelling. LANDFIRE data products are created as 30-m raster grids and are available over the internet at www.landfire.gov , accessed 22 April 2009. The data products are produced at scales that may be useful for prioritizing and planning individual hazardous fuel reduction and ecosystem restoration projects; however, the applicability of data products varies by location and specific use, and products may need to be adjusted by local users.

International Journal of Wildland Fire↗