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USGS2018

Integrating authentic scientific research in a conservation course–based undergraduate research experience

Course-based undergraduate research experiences (CUREs) have been developed to overcome barriers including students in research. However, there are few examples of CUREs that take place in a conservation and natural resource context with students engaging in field research. Here, we highlight the development of a conservation-focused CURE integrated to a research program, research benefits, student self-assessment of learning, and perception of the CURE. With the additional data, researchers were able to refine species distribution models and facilitate management decisions. Most students reported gains in their scientific skills, felt they had engaged in meaningful, real-world research. In student reflections on how this experience helped clarify their professional intentions, many reported being more likely to enroll in graduate programs and seek employment related to science. Also interesting was all students reported being more likely to talk with friends, family, or the public about wildlife conservation issues after participating, indicating that courses like this can have effects beyond the classroom, empowering students to be advocates and translators of science. Field-based, conservation-focused CUREs can create meaningful conservation and natural resource experiences with authentic scientific teaching practices.

Natural Sciences Education↗

USGS2014

The 3D Elevation Program: Summary for New Jersey

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of New Jersey, elevation data are critical for water supply and quality, flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

New Jersey↗

USGS2014

The 3D Elevation Program: summary for Indiana

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Indiana, elevation data are critical for flood risk management, agriculture and precision farming, natural resources conservation, infrastructure and construction management, aviation navigation and safety, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation's natural and constructed features.

Indiana↗

USGS2024

Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon

Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.

Oregon↗

USGS2013

The 3D Elevation Program: summary for Rhode Island

Rhode Island↗

USGS2016

Voice, perceived fairness, agency trust, and acceptance of management decisions among Minnesota anglers

Although researchers agree that public participation in natural resource decision making is critical to institutional acceptance by stakeholders and the general public, the processes to gain public perceptions of fairness, agency trust, and acceptance of management decisions are not clear. Using results from a mail survey of Minnesota resident anglers, we used structural equation modeling to examine how instrumental versus symbolic motives related to anglers’ perceptions of agency fairness, trustworthiness, and ultimately acceptance of fisheries management decisions. We applied laboratory research on relationships among procedural fairness, trust, and management acceptance, and then tested models incorporating anglers’ perceptions of voice for anglers and nonanglers in management decisions. Results suggested that trust fully mediated the relationship between procedural fairness and management acceptance. Angler perceptions of angler and nonangler voice both related to views of procedural fairness, but angler voice was more strongly related and was also significantly related to acceptance of management decisions.

Society and Natural Resources↗

USGS2006

Plans of the U.S.Geological Survey, water resources division for research, investigations, and data collection in ground water

The Geological Survey has been the foremost agency in the investigation of ground ‐ water resources in the United States beginning about 1910. Most of the basic principles of modern ground ‐ water hydrology were developed in the Survey ' s program of cooperative investigations . Use of ground water in the United States in 1960 was about 17½ percent of all water uses, excluding water power. The use will probably increase, though at a decreasing rate. Although amount of use may level off, the need to know about it will not. While coordinating its activities with those of the Office of Water Data Coordination and the Office of Water Resources Research , the Survey expects to step up its work in all three areas of data collection , investigations , and research . However, there will be changes of emphasis. Collection of raw data will tend to stress key observation points, and more and more observation of temperature and quality, including contaminants. Investigations will be aimed at upgrading reconnaissance coverage to general coverage for most of the Nation. The areal basis will be stream drainage basins and special hydrologic terranes, rather than political units. There will be an increase in the preparation of analog models for representative ground ‐ water systems. In research , the problem‐oriented basis will continue. Stress will be on basic principles that pertain to artificial recharge, and the natural recharge and discharge of ground ‐ water reservoirs; and also on the application of geologic principles on a regional scale. These are critical elements in the management of surface‐ water and ground ‐ water resources conjunctively in river basins.

Groundwater↗

USGS2013

Evaluating a multispecies adaptive management framework: Must uncertainty impede effective decision-making?

Application of adaptive management to complex natural resource systems requires careful evaluation to ensure that the process leads to improved decision-making. As part of that evaluation, adaptive policies can be compared with alternative nonadaptive management scenarios. Also, the value of reducing structural (ecological) uncertainty to achieving management objectives can be quantified. A multispecies adaptive management framework was recently adopted by the Atlantic States Marine Fisheries Commission for sustainable harvest of Delaware Bay horseshoe crabs Limulus polyphemus, while maintaining adequate stopover habitat for migrating red knots Calidris canutus rufa , the focal shorebird species. The predictive model set encompassed the structural uncertainty in the relationships between horseshoe crab spawning, red knot weight gain and red knot vital rates. Stochastic dynamic programming was used to generate a state-dependent strategy for harvest decisions given that uncertainty. In this paper, we employed a management strategy evaluation approach to evaluate the performance of this adaptive management framework. Active adaptive management was used by including model weights as state variables in the optimization and reducing structural uncertainty by model weight updating. We found that the value of information for reducing structural uncertainty is expected to be low, because the uncertainty does not appear to impede effective management. Harvest policy responded to abundance levels of both species regardless of uncertainty in the specific relationship that generated those abundances. Thus, the expected horseshoe crab harvest and red knot abundance were similar when the population generating model was uncertain or known, and harvest policy was robust to structural uncertainty as specified. Synthesis and applications . The combination of management strategy evaluation with state-dependent strategies from stochastic dynamic programming was an informative approach to evaluate adaptive management performance and value of learning. Although natural resource decisions are characterized by uncertainty, not all uncertainty will cause decisions to be altered substantially, as we found in this case. It is important to incorporate uncertainty into the decision framing and evaluate the effect of reducing that uncertainty on achieving the desired outcomes

Journal of Applied Ecology↗

USGS2014

The 3D Elevation Program: summary for Arkansas

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Arkansas, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, forest resources management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Arkansas↗

USGS2020

Conceptualizing alternate regimes in a large floodplain-river ecosystem

Regime shifts –persistent changes in the structure and function of an ecosystem - are well-documented in many ecosystems but remain poorly understood in floodplain-river ecosystems. We apply a resilience perspective to large floodplain-river ecosystems by presenting three examples of plausible sets of alternate regimes that are relevant to natural resource management interests within the Upper Mississippi River and Illinois River. These alternate regimes include: 1) a clear water and abundant vegetation regime vs. a turbid water and sparse vegetation regime in lentic, off-channel areas, 2) a diverse native fish community regime vs. an invasive-dominated fish community regime, and 3) a regime characterized by a diverse and dynamic mosaic of floodplain vegetation types vs. one characterized as a persistent invasive wet meadow monoculture. For each set of potential alternate regimes, we synthesize known or hypothesized feedback mechanisms that reinforce regimes, controlling variables that drive regime transitions, and restoration pathways. The conceptual models presented here provide a framework for synthesizing our understanding of the dynamics of this ecosystem and are relevant to other large floodplain-river ecosystems that face similar human pressures across the world. The models are currently being used to prioritize future research, test hypotheses, and inform restoration and management on the Upper Mississippi River and Illinois River. Through sharing our approach, we provide a case study in which we document an important step in operationalizing resilience concepts for the management of natural resources.

Minnesota, Wisconsin, Iowa, Illinois, Missouri↗

USGS2006

Population momentum across vertebrate life histories

Population abundance is critically important in conservation, management, and demographic theory. Thus, to better understand how perturbations to the life history affect long-term population size, we examined population momentum for four vertebrate classes with different life history strategies. In a series of demographic experiments we show that population momentum generally has a larger effect on long-term population size for organisms with long generation times than for organisms with short generation times. However, patterns between population momentum and generation time varied across taxonomic groups and according to the life history parameter that was changed. Our findings indicate that momentum may be an especially important aspect of population dynamics for long-lived vertebrates, and deserves greater attention in life history studies. Further, we discuss the importance of population momentum in natural resource management, pest control, and conservation arenas. ?? 2006 Elsevier B.V. All rights reserved.

Ecological Modelling↗

USGS2003

Modeling hyporheic zone processes

Stream biogeochemistry is influenced by the physical and chemical processes that occur in the surrounding watershed. These processes include the mass loading of solutes from terrestrial and atmospheric sources, the physical transport of solutes within the watershed, and the transformation of solutes due to biogeochemical reactions. Research over the last two decades has identified the hyporheic zone as an important part of the stream system in which these processes occur. The hyporheic zone may be loosely defined as the porous areas of the stream bed and stream bank in which stream water mixes with shallow groundwater. Exchange of water and solutes between the stream proper and the hyporheic zone has many biogeochemical implications, due to differences in the chemical composition of surface and groundwater. For example, surface waters are typically oxidized environments with relatively high dissolved oxygen concentrations. In contrast, reducing conditions are often present in groundwater systems leading to low dissolved oxygen concentrations. Further, microbial oxidation of organic materials in groundwater leads to supersaturated concentrations of dissolved carbon dioxide relative to the atmosphere. Differences in surface and groundwater pH and temperature are also common. The hyporheic zone is therefore a mixing zone in which there are gradients in the concentrations of dissolved gasses, the concentrations of oxidized and reduced species, pH, and temperature. These gradients lead to biogeochemical reactions that ultimately affect stream water quality. Due to the complexity of these natural systems, modeling techniques are frequently employed to quantify process dynamics.

Advances in Water Resources↗

USGS2006

Panel: Eco-informatics and decision making managing our natural resources

This panel responds to the December 2004 workshop on Eco-Informatics and Decision Making [1], which addressed how informatics tools can help with better management of natural resources and policy making. The workshop was jointly sponsored by the NSF, NBII, NASA, and EPA. Workshop participants recommended that informatics research in four IT areas be funded: modeling and simulation, data quality, information integration and ontologies, and social and human aspects. Additionally, they recommend that funding agencies provide infrastructure and some changes in funding habits to assure cycles of innovation in the domain were addressed. This panel brings issues raised in that workshop to the attention of digital government researchers.

Conference Paper↗

USGS2014

Adaptive management and the value of information: learning via intervention in epidemiology

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.

PLoS Biology↗

USGS2015

Model averaging and muddled multimodel inferences

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse ( Centrocercus urophasianus ) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Ecology↗

USGS2023

The 3D Elevation Program—Supporting Arkansas's economy

Introduction In recent years, Arkansas has coordinated with Federal and local partners to improve the quality and availability of high-resolution elevation data for the State. With high-quality elevation data, Arkansas can improve services offered to the public and within government, resulting in better quality of life, improved public safety, and higher return on investments. Elevation data are beneficial in numerous business activities, including agriculture and precision farming, flood risk management, geologic resource assessment and hazard mitigation, infrastructure and construction management, urban and regional planning, and natural resources conservation. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Arkansas. This fact sheet shows the status of available and in-progress 3DEP baseline lidar data in Arkansas.

Arkansas↗

USGS2005

Middle Mississippi River decision support system: user's manual

This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

Techniques and Methods↗

USGS2015

The 3D Elevation Program: summary for Connecticut

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Connecticut, elevation data are critical for coastal zone management, flood risk management, natural resources conservation, agriculture and precision farming, sea level rise and subsidence, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Connecticut↗