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At least 397 records · Page 22Linked to original sources
USGS2021

Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system

Water resource managers are faced with difficult decisions on how to satisfy human water needs while maintaining or restoring riverine ecosystems. Decision sciences have developed approaches and tools that can be used to break down difficult water management decisions into their component parts. An essential aspect of these approaches is the use of quantitative models to evaluate alternative management strategies. Here, we describe four integrated decision support models for evaluating the effect of flows on two life history stages of Chinook salmon ( Oncorhynchus tshawytscha ) and Steelhead ( O. mykiss ). We then use constrained nonlinear optimization to identify optimal flow regimes for the water year type with the least available water. These flow regimes were then used by managers to develop candidate minimum flow strategies that were evaluated using forward simulation and sensitivity analyses. We found that optimal flow regimes differed markedly from existing regulations and varied among species and life history stages. However, evaluation of tradeoffs among the four competing objectives indicated relatively minimal losses for most objectives when the optimal flows were based on equally weighting the objectives. Sensitivity analysis indicated that water temperature was the primary driver of estimated outcomes and suggested that managers consider alternative means of managing temperatures. Decision sciences have created multiple analytical tools and approaches that simplify complex problems, such as water resource management, and we believe that water resource management would benefit from their increased use.

Oregon↗
USGS2011

Application of the CO2-PENS risk analysis tool to the Rock Springs Uplift, Wyoming

We describe preliminary application of the CO 2 -PENS performance and risk analysis tool to a planned geologic CO 2 sequestration demonstration project in the Rock Springs Uplift (RSU), located in south western Wyoming. We use data from the RSU to populate CO 2 -PENS, an evolving system-level modeling tool developed at Los Alamos National Laboratory. This tool has been designed to generate performance and risk assessment calculations for the geologic sequestration of carbon dioxide. Our approach follows Systems Analysis logic and includes estimates of uncertainty in model parameters and Monte-Carlo simulations that lead to probabilistic results. Probabilistic results provide decision makers with a range in the likelihood of different outcomes. Herein we present results from a newly implemented approach in CO 2 -PENS that captures site-specific spatially coherent details such as topography on the reservoir/cap-rock interface, changes in saturation and pressure during injection, and dip on overlying aquifers that may be impacted by leakage upward through wellbores and faults. We present simulations of CO 2 injection under different uncertainty distributions for hypothetical leaking wells and faults. Although results are preliminary and to be used only for demonstration of the approach, future results of the risk analysis will form the basis for a discussion on methods to reduce uncertainty in the risk calculations. Additionally, we present ideas on using the model to help locate monitoring equipment to detect potential leaks. By maintaining site-specific details in the CO 2 -PENS analysis we provide a tool that allows more logical presentations to stakeholders in the region.

Energy Procedia↗
USGS2016

Regional analysis of social characteristics for evacuation resource planning: ARkStorm scenario

Local planning is insufficient for regional catastrophes; regional exercises are needed to test emergency plans and decision-making structures. The ARkStorm scenario would trigger a mass evacuation that would be complicated by the social characteristics of populations [e.g., vehicle ownership, age, poverty, English language limitation (ELL), and shelter needs]. Land cover data and dasymetric mapping improves the allocation of residential populations and their social characteristics to the ARkStorm flood zone in 21 counties in California. Numbers and concentrations of county, urban, and rural residents exposed to flooding as well as populations in and out of the scenario flood zone are profiled. The results inform mass evacuation planning by providing a means to (1) examine the sufficiency of mutual aid agreements, (2) underscore planning for carless populations, and (3) tailor multilingual communication strategies. The various geographical distinctions emphasize different challenges throughout the region. It will be important to investigate behavioral responses to warnings, identify evacuation constraints (e.g., shelter capacity versus need), and obtain comparable data on transient populations.

Natural Hazards Review↗
USGS2014

Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA

1. Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns. 2. We conducted modularity analyses of networks surrounding a rare endemic annual plant, Eriogonum visheri , at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species. 3. Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on E. visheri . Sharing a module increased risk of interspecific pollen transfer to E. visheri . Control of invasive Salsola tragus , which shared a module with E. visheri , is therefore a prudent management objective, but lack of control of invasive Melilotus officinalis , which occupied a different module, is unlikely to negatively affect pollination of E. visheri . Eriogonum pauciflorum may occupy a key position in this network, supporting insects from the E. visheri module when E. visheri is less abundant. 4. Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis. 5. Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as E. pauciflorum in our study.

South Dakota↗
USGS2008

Non-random temporary emigration and the robust design: Conditions for bias at the end of a time series: Section VIII

Deviations from model assumptions in the application of capture–recapture models to real life situations can introduce unknown bias. Understanding the type and magnitude of bias under these conditions is important to interpreting model results. In a robust design analysis of long-term photo-documented sighting histories of the endangered Florida manatee, I found high survival rates, high rates of non-random temporary emigration, significant time-dependence, and a diversity of factors affecting temporary emigration that made it difficult to model emigration in any meaningful fashion. Examination of the time-dependent survival estimates indicated a suspicious drop in survival rates near the end of the time series that persisted when the original capture histories were truncated and reanalyzed under a shorter time frame. Given the wide swings in manatee emigration estimates from year to year, a likely source of bias in survival was the convention to resolve confounding of the last survival probability in a time-dependent model with the last emigration probabilities by setting the last unmeasurable emigration probability equal to the previous year’s probability when the equality was actually false. Results of a series of simulations demonstrated that if the unmeasurable temporary emigration probabilities in the last time period were not accurately modeled, an estimation model with significant annual variation in survival probabilities and emigration probabilities produced bias in survival estimates at the end of the study or time series being explored. Furthermore, the bias propagated back in time beyond the last two time periods and the number of years affected varied positively with survival and emigration probabilities. Truncating the data to a shorter time frame and reanalyzing demonstrated that with additional years of data surviving temporary emigrants eventually return and are detected, thus in subsequent analysis unbiased estimates are eventually realized. Knowing the extent and magnitude of the potential bias can help in making decisions as to what time frame provides the best estimates or the most reliable opportunity to model and test hypotheses about factors affecting survival probability. To assess bias, truncating the capture histories to shorter time frames and reanalyzing the data to compare time-specific estimates may help identify spurious effects. Running simulations that mimic the parameter values and movement conditions in the real situation can provide estimates of standardized bias that can be used to identify those annual estimates that are biased to the point where the 95% confidence intervals are inadequate in describing the uncertainty of the estimates.

Book chapter↗
USGS2014

Landbird trends in national parks of the North Coast and Cascades Network, 2005-12

National parks in the North Coast and Cascades Network (NCCN) can fulfill vital roles as refuges for bird species dependent on late-successional forest conditions and as reference sites for assessing the effects of land-use and land-cover changes on bird populations throughout the larger Pacific Northwest region. Additionally, long-term monitoring of landbirds throughout the NCCN provides information that can inform decisions about important management issues in the parks, including visitor impacts, fire management, and the effects of introduced species. In 2005, the NCCN began implementing a network-wide Landbird Monitoring Project as part of the NPS Inventory and Monitoring Program. In this report, we discuss 8-year trends (2005–12) of bird populations in the NCCN, based on a sampling framework of point counts established in three large wilderness parks (Mount Rainier, North Cascades, and Olympic National Parks), 7-year trends at Lewis and Clark National Historical Park (sampled in 2006, 2008, 2010, and 2012), and 5-year trends at San Juan Islands National Historical Park (sampled in 2007, 2009, and 2011). Our analysis encompasses a fairly short time span for this long-term monitoring program. The first 2 years of the time series (2005 and 2006) were implemented as part of a limited pilot study that included only a small subset of the transects. The subsequent 6 years (2007–12) represent just a single cycle through 5 years of alternating panels of transects in the large parks, with the first of five alternating panels revisited for the first time in 2012. Of 204 transects that comprise the six sampling panels in the large parks, only 68 (one-third) have thus been eligible for revisit surveys (34 during every year after 2005, and an additional 34 only in 2012) and can contribute to our current trend estimates. We therefore initiated the current analysis with a primary goal of testing our analytical procedures rather than detecting trends that might be strong enough to drive conservation or management decisions in the parks or elsewhere. We expect that aggregated trend detection results may change substantially over the next several years, as the number of transects with revisit histories triples and the spatial dispersion of transects contributing to trend estimates also improves greatly. In the meantime, caution should be exercised in interpreting the importance of trends, as individual years can have very large influences on the direction and magnitude of trends in a time series of such limited duration (and limited numbers of repeat visits at the small parks). Nevertheless, we estimated trends for 43 species at Mount Rainier National Park, 53 species at North Cascades National Park Complex, and 41 species at Olympic National Park. Of 137 park-species combinations (including combined-park analyses), we found 16 significant decreases (12 percent) and five significant increases (4 percent). We identify several limitations of the current analytical framework for trend assessment but suggest that the overall sampling design is strong and amenable to analysis by more recently developed model-based methods. These could provide a more flexible framework for examining trends and other population parameters of interest, as well as testing hypotheses that relate the distribution and abundance of species to environmental covariates. A model-based approach would allow for modeling various components of the detection process and analyzing observations (detection process), population state (occupancy, population size, density), and change (trend, local extinction and colonization rates turnover) simultaneously. Finally, we also evaluate operational aspects of NCCN Landbird Monitoring Project, and conclude that our robust, multi-party partnership is successfully implementing the project as it was envisioned.

British Columbia;Oregon;Washington↗
USGS2012

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Missouri River↗
USGS2012

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: An example from the Missouri River

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Montana, Nebraska, North Dakota, South Dakota↗
USGS2024

Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?

One of the flagship products from the U.S. Geological Survey (USGS) is the National Seismic Hazard Model (NSHM). Since 1976, the NSHM has been periodically updated to reflect newly published earthquake science and provide probabilistic estimates of seismic hazard for the United States. During each update cycle, alternative models are deliberated, analyzed, and documented through logic trees and their corresponding logic tree branch weights. For example, the decision to modify a logic tree branch weight may be influenced by sensitivity analyses of the logic tree branches in their effects on the mean hazard. However, do small changes in traditional measures of hazard imply small changes in risk? In this study, we make use of two update cycles of the USGS NSHMs and a National Bridge Inventory (NBI) from the Federal Highway Administration (FHWA) to explore the preceding question. Specifically, we first identify geographic locations in the conterminous United States in which the change in hazard from one cycle to another is relatively small. Next, we model the seismic risk to highway bridges for these locations and for each update cycle, while simultaneously distinguishing low hazard environments from high hazard environments. These data enable quantitative analysis of how much changes in risk can be expected given small changes in hazard, investigating the importance of risk models in decision-making during development of the USGS NSHMs.

Conference Paper↗
USGS2025

Reevaluation of an adaptive management framework for invasive Grass Carp within Lake Erie

Objective Response efforts to control invasive species frequently require making decisions in the face of substantial uncertainty. Adaptive management, which emphasizes learning during the process of managing, can be useful in cases where uncertainty impedes the decision-making process. Here, we describe how technical and institutional learning led to reformulating decision-making elements, known as double-loop learning, and how uncertainty stemming from a lack of knowledge influenced the selection of alternative strategies in an ongoing adaptive management process for invasive Grass Carp Ctenopharyngodon idella in Lake Erie. Methods When response efforts began, little was known about the population dynamics, ecology, and biology of Grass Carp within the lake. The availability of funding for sustained response efforts was also unknown. A network population model was constructed that relied heavily on values and estimates from limited data to project adult Grass Carp abundance in Lake Erie and evaluate the ability of various response strategies to achieve the desired objectives. After this initial assessment, the collection of new information was emphasized as response efforts increased to aid future assessments. With this expanded knowledge and including additional input from stakeholders, we modified the population model, evaluated new response scenarios, refined objectives, and examined the influence of uncertainty (parameter and expert opinion) on Grass Carp response efforts. Results Under uncertainty of population model parameters and expert opinion, the value-of-information analysis revealed that uncertainties in spawning deterrent efficacy, survival, and the underlying stock–recruitment relationship were important and could change the preferred decision. The efficiency of spawning deterrents influenced the preferred decision outcome among alternative strategies, particularly when >80% of fish were allowed to pass and spawn, indicating that a deterrent may not be worth implementing if passing rates are above this threshold. Conclusions We thereby demonstrate the benefits for invasive species management programs of implementing learning and resolving uncertainties within an adaptive management framework to improve decision making.

Lake Erie↗
USGS2011

Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography

Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.

Journal of Ornithology↗
USGS1995

1995 annual report on Alaska's mineral resources

Section 1011 of the Alaska National Interest Lands Conservation Act (ANILCA) of 1980, as amended, requires that "On or before October 1, 1982, and annually thereafter, the President shall transmit to the Congress all pertinent public information relating to minerals in Alaska gathered by the United States Geological Surveys, United States Bureau of Mines, and any other Federal agency." This report has been prepared in response to that requirement. This circular is the fourteenth in the series of annual mineral reports mandated by the ANILCA. The report provides information about current Alaskan mineral projects and events during 1994; the emphasis is on Federal activity. The report addresses both onshore and offshore areas of Alaska. The U.S. Geological Survey (USGS), U.S. Bureau of Mines (USBM), and Minerals Management Service (MMS) are the principal Federal agencies that publish information about energy and mineral resources in Alaska. Their reports and data form the basis for decisions by other Federal agencies regarding land use, access, environmental impacts, and mining claim evaluation. The time required for sample analysis, data synthesis, and publication is lengthy; as a result, scientific reports are generally issued a year or more after initial sample and data collection. Other sources of information for this report include additional Federal and State publications, trade and professional journals, presentations at public meetings and hearings, and press releases. Information is provided for two broad categories of minerals: energy resources and nonfuel-mineral resources.

Circular↗
USGS2017

Precipitation thresholds for landslide occurrence near Seattle, Mukilteo, and Everett, Washington

Shallow landslides along coastal bluffs frequently occur in the railway corridor between Seattle and Everett, Washington. These slides disrupt passenger rail service, both because of required track maintenance and because the railroad owner, Burlington Northern Santa Fe Railway, does not allow passenger travel for 48 hours after a disruptive landslide. Sound Transit, which operates commuter trains in the corridor, is interested in a decision-making tool to help preemptively cancel passenger railway service in dangerous conditions and reallocate resources to alternative transportation. Statistical analysis showed that a majority of landslides along the Seattle-Everett Corridor are strongly correlated with antecedent rainfall, but that 21-37 percent of recorded landslide dates experienced less than 1 inch of precipitation in the 3 days preceding the landslide and less than 4 inches of rain in the 15 days prior to the preceding 3 days. We developed two empirical thresholds to identify precipitation conditions correlated with landslide occurrence. The two thresholds are defined as P 3 = 2.16-0.44P 15 and P 3 = 2.16-0.22P 32 , where P 3 is the cumulative precipitation in the 3 days prior to the considered date and P 15 or P 32 is the cumulative precipitation in the 15 days or 32 days prior to P 3 (all measurements given in inches). The two thresholds, when compared to a previously developed threshold, quantitatively improve the prediction rate. We also investigated rainfall intensity-duration (ID) thresholds to determine whether revision would improve identification of moderate-intensity, landslide-producing storms. New, optimized ID thresholds evaluate rainstorms lasting at least 12 hours and identify landslide-inducing storms that were typically missed by previously published ID thresholds. The main advantage of the ID thresholds appears when they are combined with recent-antecedent thresholds because rainfall conditions that exceed both threshold types are more likely to induce two or more landslides than conditions that exceed only one threshold type.

Washington↗
USGS2009

Occupancy estimation and the closure assumption

1. Recent advances in occupancy estimation that adjust for imperfect detection have provided substantial improvements over traditional approaches and are receiving considerable use in applied ecology. To estimate and adjust for detectability, occupancy modelling requires multiple surveys at a site and requires the assumption of 'closure' between surveys, i.e. no changes in occupancy between surveys. Violations of this assumption could bias parameter estimates; however, little work has assessed model sensitivity to violations of this assumption or how commonly such violations occur in nature. 2. We apply a modelling procedure that can test for closure to two avian point-count data sets in Montana and New Hampshire, USA, that exemplify time-scales at which closure is often assumed. These data sets illustrate different sampling designs that allow testing for closure but are currently rarely employed in field investigations. Using a simulation study, we then evaluate the sensitivity of parameter estimates to changes in site occupancy and evaluate a power analysis developed for sampling designs that is aimed at limiting the likelihood of closure. 3. Application of our approach to point-count data indicates that habitats may frequently be open to changes in site occupancy at time-scales typical of many occupancy investigations, with 71% and 100% of species investigated in Montana and New Hampshire respectively, showing violation of closure across time periods of 3 weeks and 8 days respectively. 4. Simulations suggest that models assuming closure are sensitive to changes in occupancy. Power analyses further suggest that the modelling procedure we apply can effectively test for closure. 5. Synthesis and applications. Our demonstration that sites may be open to changes in site occupancy over time-scales typical of many occupancy investigations, combined with the sensitivity of models to violations of the closure assumption, highlights the importance of properly addressing the closure assumption in both sampling designs and analysis. Furthermore, inappropriately applying closed models could have negative consequences when monitoring rare or declining species for conservation and management decisions, because violations of closure typically lead to overestimates of the probability of occurrence.

Montana;New Hampshire↗
USGS2015

Classification of rocky headlands in California with relevance to littoral cell boundary delineation

Despite extensive studies of hydrodynamics and sediment flux along beaches, there is little information on the processes, pathways and timing of water and sediment transport around rocky headlands. In this study, headlands along the California coast are classified to advance understanding of headland dynamics and littoral cell boundaries in support of improved coastal management decisions. Geomorphological parameters for 78 headlands were quantified from geological maps, remote-sensing imagery, navigational charts, and shoreline geospatial databases. K -means cluster analysis grouped the headlands into eight distinct classes based on headland perimeter, bathymetric slope ratio, and the headland apex angle. Wave data were used to investigate the potential for sediment transport around the headland types and determine the efficacy of the headland as a littoral cell boundary. Four classes of headland appear to function well as littoral cell boundaries, with headland size (e.g., perimeter or area) and a marked change in nearshore bathymetry across the headland being relevant attributes. About half of the traditional California littoral cell boundaries align with headland classes that are expected to perform poorly in blocking alongshore sediment transport, calling into question these boundaries. Better definition of these littoral cell boundaries is important for regional sediment management decisions.

California↗
USGS2017

Multiscale guidance and tools for implementing a landscape approach to resource management in the Bureau of Land Management

The Bureau of Land Management (BLM) is implementing a landscape approach to resource management (hereafter, landscape approach) to more effectively work with partners and understand the effects of management decisions. A landscape approach is a set of concepts and principles used to guide resource management when multiple stakeholders are involved and goals include diverse and sustainable social, environmental, and economic outcomes. Core principles of a landscape approach include seeking meaningful participation of diverse stakeholders, considering diverse resource values in multifunctional landscapes, acknowledging the tradeoffs needed to meet diverse objectives in the context of sustainable resource management, and addressing the complexity of social and ecological processes by embracing interdisciplinarity and considering multiple and broad spatial and temporal perspectives. In chapter 1, we outline the overall goal of this report: to provide a conceptual foundation and framework for implementing a landscape approach to resource management in the BLM, focusing on the role of multiscale natural resource monitoring and assessment information. In chapter 2, we describe a landscape approach to resource management. BLM actions taken to implement a landscape approach include a major effort to compile broad-scale data on natural resource status and condition across much of the west. These broadscale data now provide a regional context for interpreting monitoring data collected at individual sites and informing decisions made for local projects. We also illustrate the utility of using multiscale data to understand potential effects of different resource management decisions, define relevant terms in landscape ecology, and identify spatial scales at which planning and management decisions may be evaluated. In chapter 3, we describe how the BLM Rapid Ecoregional Assessment program and Assessment, Inventory and Monitoring program may be integrated to provide the multiscale monitoring data needed to inform a landscape approach. We propose six core, broad-scale indicators of natural resource status and condition: the amount, spatial distribution, patch size and connectivity of ecosystems and wildlife habitats, and the pattern of existing development across the landscape. Additional supplemental broad-scale indicators may include fire return intervals, distributions of invasive species, and vulnerability of ecosystems to a changing climate. Landscape intactness is an additional derived indicator that is calculated from one or more of the core and supplemental broad-scale indicators. We then outline a process for assessing broad-scale indicators that is consistent with the overall BLM Assessment, Inventory, and Monitoring process, facilitating development of a multiscale natural resource monitoring program. Finally, we describe how broad-scale indicators of natural resource status and condition may guide field monitoring implemented through the BLM Assessment, Inventory and Monitoring program and help address complex management questions. In chapter 4, we consider the specific question of assessing the ecological integrity of rangelands across the western United States. We first define ecological integrity and its relation to land health. We then suggest that a combination of six local-scale indicators collected through field sampling at individual sites and five complementary broad-scale indicators together provide information on the composition, structure, and function of rangelands. The terrestrial monitoring indicators collected at the level of individual field sites are the amount of bare ground, vegetation composition (including invasive plants and plants of management concern), vegetation height, and the proportion of the soil surface in large intercanopy gaps. The broad-scale indicators are vegetation amount, distribution, patch size, connectivity, and productivity, along with the pattern of terrestrial development. Our suggested approach to quantifying ecological integrity focuses specifically on informing management of public lands for multiple resource uses, and illustrates how existing data collected through BLM monitoring and assessment programs may be used together to provide multiscale information on land condition across broad extents. In chapter 5, we develop a method for quantifying landscape intactness and apply this method to the western United States. Our multiscale index of landscape intactness is designed to be defensible, decomposable, and easy to understand. The foundation of the multiscale index of landscape intactness is the surface disturbance footprint of anthropogenic development, including energy and urban development, roads and railroads, cultivated croplands, surface mines and quarries, and energy transmission lines and pipelines. The index represents a gradient of anthropogenic influence as represented by development summarized at two spatial scales of analysis: 2.5 and 20 kilometers. We provide several example applications of the index, illustrating how these data may inform natural resource decisions at the spatial extent of BLM field and district offices, states, ecoregions, and the western United States. We find that 19.2 percent of lands managed by the BLM across the 17 western states of the conterminous United States had the highest landscape intactness. The largest intact areas occur on public lands at high elevations or in the Great Basin. We believe the frameworks, processes, and analyses provided in this report will improve the ability of the BLM to identify and evaluate potential direct and indirect effects of management actions (such as habitat restoration and renewable energy development), and assist the BLM in further implementing a landscape approach to resource management.

Open-File Report↗
USGS2014

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

Estuaries and Coasts↗
USGS2017

The value of information for woodland management: Updating a state–transition model

Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.

Victoria↗