Geology topics

James D. Nichols

Publications and source records attributed to James D. Nichols.

At least 55 records · Page 3Linked to original sources

USGS2015

Heterogeneous movement of insectivorous Amazonian birds through primary and secondary forest: A case study using multistate models with radiotelemetry data

Given rates of deforestation, disturbance, and secondary forest accumulation in tropical rainforests, there is a great need to quantify habitat use and movement among different habitats. This need is particularly pronounced for animals most sensitive to disturbance, such as insectivorous understory birds. Here we use multistate capture–recapture models with radiotelemetry data to determine the successional stage at which within-day movement probabilities of Amazonian birds in secondary forest are similar to those in primary forest. We radio-tracked three common understory insectivore species in primary and secondary forest at the Biological Dynamics of Forest Fragments project near Manaus, Brazil: two woodcreepers, Glyphorynchus spirurus ( n = 19) and Xiphorhynchus pardalotus ( n = 18), and the terrestrial antthrush Formicarius colma ( n = 19 ) . Forest age was a strong predictor of fidelity to a given habitat. All three species showed greater fidelity to primary forest than to 8–14-year-old secondary forest, indicating the latter’s relatively poor quality. The two woodcreeper species used 12–18-year-old secondary forest in a manner comparable to continuous forest, but F . colma avoided moving even to 27–31-year-old secondary forest—the oldest at our site. Our results suggest that managers concerned with less sensitive species can assume that forest reserves connected by 12–18-year-old secondary forest corridors are effectively connected. On the other hand, >30 years are required after land abandonment before secondary forest serves as a primary forest-like conduit for movement by F . colma ; more sensitive terrestrial insectivores may take longer still.

Manaus↗

USGS2015

To predict the niche, model colonization and extinction

Ecologists frequently try to predict the future geographic distributions of species. Most studies assume that the current distribution of a species reflects its environmental requirements (i.e., the species' niche). However, the current distributions of many species are unlikely to be at equilibrium with the current distribution of environmental conditions, both because of ongoing invasions and because the distribution of suitable environmental conditions is always changing. This mismatch between the equilibrium assumptions inherent in many analyses and the disequilibrium conditions in the real world leads to inaccurate predictions of species' geographic distributions and suggests the need for theory and analytical tools that avoid equilibrium assumptions. Here, we develop a general theory of environmental associations during periods of transient dynamics. We show that time-invariant relationships between environmental conditions and rates of local colonization and extinction can produce substantial temporal variation in occupancy–environment relationships. We then estimate occupancy–environment relationships during three avian invasions. Changes in occupancy–environment relationships over time differ among species but are predicted by dynamic occupancy models. Since estimates of the occupancy–environment relationships themselves are frequently poor predictors of future occupancy patterns, research should increasingly focus on characterizing how rates of local colonization and extinction vary with environmental conditions.

Ecology↗

USGS2014

Multiseason occupancy models for correlated replicate surveys

Occupancy surveys collecting data from adjacent (sometimes correlated) spatial replicates have become relatively popular for logistical reasons. Hines et al . ( 2010 ) presented one approach to modelling such data for single-season occupancy surveys. Here, we present a multiseason analogue of this model (with corresponding software) for inferences about occupancy dynamics. We include a new parameter to deal with the uncertainty associated with the first spatial replicate for both single-season and multiseason models. We use a case study, based on the brown-headed nuthatch, to assess the need for these models when analysing data from the North American Breeding Bird Survey (BBS), and we test various hypotheses about occupancy dynamics for this species in the south-eastern United States. The new model permits inference about local probabilities of extinction, colonization and occupancy for sampling conducted over multiple seasons. The model performs adequately, based on a small simulation study and on results of the case study analysis. The new model incorporating correlated replicates was strongly favoured by model selection for the BBS data for brown-headed nuthatch ( Sitta pusilla ). Latitude was found to be an important source of variation in local colonization and occupancy probabilities for brown-headed nuthatch, with both probabilities being higher near the centre of the species range, as opposed to more northern and southern areas. We recommend this new occupancy model for detection–nondetection studies that use potentially correlated replicates.

North Carolina, South Carolina, Florida, Georgia↗

USGS2014

Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph

Metapopulation ecology is a field that is richer in theory than in empirical results. Many existing empirical studies use an incidence function approach based on spatial patterns and key assumptions about extinction and colonization rates. Here we recast these assumptions as hypotheses to be tested using 18 years of historic detection survey data combined with four years of data from a new monitoring program for the Lower Keys marsh rabbit. We developed a new model to estimate probabilities of local extinction and colonization in the presence of nondetection, while accounting for estimated occupancy levels of neighboring patches. We used model selection to identify important drivers of population turnover and estimate the effective neighborhood size for this system. Several key relationships related to patch size and isolation that are often assumed in metapopulation models were supported: patch size was negatively related to the probability of extinction and positively related to colonization, and estimated occupancy of neighboring patches was positively related to colonization and negatively related to extinction probabilities. This latter relationship suggested the existence of rescue effects. In our study system, we inferred that coastal patches experienced higher probabilities of extinction and colonization than interior patches. Interior patches exhibited higher occupancy probabilities and may serve as refugia, permitting colonization of coastal patches following disturbances such as hurricanes and storm surges. Our modeling approach should be useful for incorporating neighbor occupancy into future metapopulation analyses and in dealing with other historic occupancy surveys that may not include the recommended levels of sampling replication.

Florida↗

USGS2014

Application of threshold concepts to ecological management problems: Occupancy of Golden Eagles in Denali National Park, Alaska

In this chapter, we demonstrate the application of the various classes of thresholds, detailed in earlier chapters and elsewhere, via an actual but simplified natural resource management case study. We intend our example to provide the reader with the ability to recognize and apply the theoretical concepts of utility, ecological and decision thresholds to management problems through a formalized decision-analytic process. Our case study concerns the management of human recreational activities in Alaska’s Denali National Park, USA, and the possible impacts of such activities on nesting Golden Eagles, Aquila chrysaetos. Managers desire to allow visitors the greatest amount of access to park lands, provided that eagle nesting-site occupancy is maintained at a level determined to be acceptable by the managers themselves. As these two management objectives are potentially at odds, we treat minimum desired occupancy level as a utility threshold which, then, serves to guide the selection of annual management alternatives in the decision process. As human disturbance is not the only factor influencing eagle occupancy, we model nesting-site dynamics as a function of both disturbance and prey availability. We incorporate uncertainty in these dynamics by considering several hypotheses, including a hypothesis that site occupancy is affected only at a threshold level of prey abundance (i.e., an ecological threshold effect). By considering competing management objectives and accounting for two forms of thresholds in the decision process, we are able to determine the optimal number of annual nesting-site restrictions that will produce the greatest long-term benefits for both eagles and humans. Setting a utility threshold of 75 occupied sites, out of a total of 90 potential nesting sites, the optimization specified a decision threshold at approximately 80 occupied sites. At the point that current occupancy falls below 80 sites, the recommended decision is to begin restricting access to humans; above this level, it is recommended that all eagle territories be opened to human recreation. We evaluated the sensitivity of the decision threshold to uncertainty in system dynamics and to management objectives (i.e., to the utility threshold).

Alaska↗

USGS2014

Accounting for false-positive acoustic detections of bats using occupancy models

1. Acoustic surveys have become a common survey method for bats and other vocal taxa. Previous work shows that bat echolocation may be misidentified, but common analytic methods, such as occupancy models, assume that misidentifications do not occur. Unless rare, such misidentifications could lead to incorrect inferences with significant management implications. 2. We fit a false-positive occupancy model to data from paired bat detector and mist-net surveys to estimate probability of presence when survey data may include false positives. We compared estimated occupancy and detection rates to those obtained from a standard occupancy model. We also derived a formula to estimate the probability that bats were present at a site given its detection history. As an example, we analysed survey data for little brown bats Myotis lucifugus from 135 sites in Washington and Oregon, USA. 3. We estimated that at an unoccupied site, acoustic surveys had a 14% chance per night of producing spurious M. lucifugus detections. Estimated detection rates were higher and occupancy rates were lower under the false-positive model, relative to a standard occupancy model. Un-modelled false positives also affected inferences about occupancy at individual sites. For example, probability of occupancy at individual sites with acoustic detections but no captures ranged from 2% to 100% under the false-positive occupancy model, but was always 100% under a standard occupancy model. 4. Synthesis and applications. Our results suggest that false positives sufficient to affect inferences may be common in acoustic surveys for bats. We demonstrate an approach that can estimate occupancy, regardless of the false-positive rate, when acoustic surveys are paired with capture surveys. Applications of this approach include monitoring the spread of White-Nose Syndrome, estimating the impact of climate change and informing conservation listing decisions. We calculate a site-specific probability of occupancy, conditional on survey results, which could inform local permitting decisions, such as for wind energy projects. More generally, the magnitude of false positives suggests that false-positive occupancy models can improve accuracy in research and monitoring of bats and provide wildlife managers with more reliable information.

Oregon, Washington↗

USGS2014

Tailoring point counts for inference about avian density: dealing with nondetection and availability

Point counts are commonly used for bird surveys, but interpretation is ambiguous unless there is an accounting for the imperfect detection of individuals. We show how repeated point counts, supplemented by observation distances, can account for two aspects of the counting process: (1) detection of birds conditional on being available for observation and (2) the availability of birds for detection given presence. We propose a hierarchical model that permits the radius in which birds are available for detection to vary with forest stand age (or other relevant habitat features), so that the number of birds available at each location is described by a Poisson-gamma mixture. Conditional on availability, the number of birds detected at each location is modeled by a beta-binomial distribution. We fit this model to repeated point count data of Florida scrub-jays and found evidence that the area in which birds were available for detection decreased with increasing stand age. Estimated density was 0.083 (95%CI: 0.060–0.113) scrub-jays/ha. Point counts of birds have a number of appealing features. Based on our findings, however, an accounting for both components of the counting process may be necessary to ensure that abundance estimates are comparable across time and space. Our approach could easily be adapted to other species and habitats.

Natural Resource Modeling↗

USGS2014

The roles of competition and habitat in the dynamics of populations and species distributions

The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition's importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading (barred owl: Strix varia) and a resident species (Northern spotted owl: Strix occidentalis caurina) in a 1000 km2 study area over a 22 - year period. Past studies of these competitors have focused on the dynamics of one species at a time, hindering efforts to parse out the roles of habitat and competition and to forecast the future of the resident species. In addition, while these studies accounted for the imperfect detection of the focal species, no multiseason analysis of these species has accounted for the imperfect detection of the secondary species, potentially biasing inference. We analyze survey data using models that combine the general multistate-multiseason occupancy modeling framework with autologistic modeling - allowing us to account for important aspects of our study system. We find that local extinction probability increases for each species when the other is present; however, the effect of the invader on the resident is greater. Although the species prefer different habitats, these habitats are highly correlated at the patch scale and the impacts of invader on the resident are greatest in patches that would otherwise be optimal. As a consequence, competition leads to a weaker relationship between habitat and Northern spotted owl occupancy. Colonization and extinction rates of the invader are closely related to neighborhood occupancy, and over the first half of the study the availability of colonists limited the rate of population growth. Competition is likely to exclude the resident species both through its immediate effects on local extinction, and by indirectly lowering colonization rates as Northern spotted owl occupancy declines. Our analysis suggests that dispersal limitation affects both the invasion dynamics and the scale at which the effects of competition are observed. We also provide predictions regarding the potential costs and benefits of managing barred owl populations at different target levels.

Oregon↗

USGS2014

Age-specific survival of male golden-cheeked warblers on the Fort Hood Military Reservation, Texas

Population models are essential components of large-scale conservation and management plans for the federally endangered Golden-cheeked Warbler ( Setophaga chrysoparia ; hereafter GCWA). However, existing models are based on vital rate estimates calculated using relatively small data sets that are now more than a decade old. We estimated more current, precise adult and juvenile apparent survival (Φ) probabilities and their associated variances for male GCWAs. In addition to providing estimates for use in population modeling, we tested hypotheses about spatial and temporal variation in Φ. We assessed whether a linear trend in Φ or a change in the overall mean Φ corresponded to an observed increase in GCWA abundance during 1992-2000 and if Φ varied among study plots. To accomplish these objectives, we analyzed long-term GCWA capture-resight data from 1992 through 2011, collected across seven study plots on the Fort Hood Military Reservation using a Cormack-Jolly-Seber model structure within program MARK. We also estimated Φ process and sampling variances using a variance-components approach. Our results did not provide evidence of site-specific variation in adult Φ on the installation. Because of a lack of data, we could not assess whether juvenile Φ varied spatially. We did not detect a strong temporal association between GCWA abundance and Φ. Mean estimates of Φ for adult and juvenile male GCWAs for all years analyzed were 0.47 with a process variance of 0.0120 and a sampling variance of 0.0113 and 0.28 with a process variance of 0.0076 and a sampling variance of 0.0149, respectively. Although juvenile Φ did not differ greatly from previous estimates, our adult Φ estimate suggests previous GCWA population models were overly optimistic with respect to adult survival. These updated Φ probabilities and their associated variances will be incorporated into new population models to assist with GCWA conservation decision making.

Texas↗

USGS2014

Thresholds for conservation and management: structured decision making as a conceptual framework

A conceptual framework is provided for considering the threshold concept in natural resource management and conservation. We define three kinds of thresholds relevant to management and conservation. Ecological thresholds are values of system state variables at which small changes bring about substantial or specified changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Book↗

USGS2014

The effects of harvest on waterfowl populations

Change in the size of populations over space and time is, arguably, the motivation for much of pure and applied ecological research. The fundamental model for the dynamics of any population is straightforward: the net change in the abundance is the simple difference between the number of individuals entering the population and the number leaving the population, either or both of which may change in response to factors intrinsic and extrinsic to the population. While harvest of individuals from a population constitutes a clear extrinsic source of removal of individuals, the response of populations to harvest is frequently complex, reflecting an interaction of harvest with one or more population processes. Here we consider the role of these interactions, and factors influencing them, on the effective harvest management of waterfowl populations. We review historical ideas concerning harvest and discuss the relationship(s) between waterfowl life histories and the development and application of population models to inform harvest management. The influence of population structure (age, spatial) on derivation of optimal harvest strategies (with and without explicit consideration of various sources of uncertainty) is considered. In addition to population structure, we discuss how the optimal harvest strategy may be influenced by: 1) patterns of density-dependence in one or more vital rates, and 2) heterogeneity in vital rates among individuals within an age-sex-size class. Although derivation of the optimal harvest strategy for simple population models (with or without structure) is generally straightforward, there are several potential difficulties in application. In particular, uncertainty concerning the population structure at the time of harvest, and the ability to regulate the structure of the harvest itself, are significant complications. We therefore review the evidence of effects of harvest on waterfowl populations. Some of this evidence has focussed on correspondence of data with more phenomenological models and other evidence relates to specific mechanisms, including densitydependence and heterogeneity. An important part of this evidence is found in the evolution of model weights under various adaptive harvest management programmes of the U.S. Fish and Wildlife Service for North American waterfowl. Overall, there is substantial uncertainty about system dynamics, about the impacts of potential management and conservation decisions on those dynamics, and how to optimise management decisions in the presence of such uncertainties. Such relationships are unlikely to be stationary over space or time, and selective harvest of some individuals can potentially alter life history allocation of resources over time – both of which will potentially influence optimal harvest strategies. These sources of variation and uncertainty argue for the use of adaptive approaches to waterfowl harvest management.

Wildfowl↗

USGS2014

USGS ecosystem research for the next decade: advancing discovery and application in parks and protected areas through collaboration

Ecosystems within parks and protected areas in the United States and throughout the world are being transformed at an unprecedented rate. Changes associated with natural hazards, greenhouse gas emissions, and increasing demands for water, food, land, energy and mineral resources are placing urgency on sound decision making that will help sustain our Nation’s economic and environmental well-being (Millennium Ecosystem Assessment, 2005). In recognition of the importance of science in making these decisions, the U.S. Geological Survey (USGS) in 2007 identified ecosystem science as one of six science directions included in a comprehensive decadal strategy (USGS 2007). The Ecosystems Mission Area was identified as essential for integrating activity within the USGS and as a key to enhanced integration with other Federal and private sector research and management organizations (Myers at al., 2007). This paper focuses on benefits to parks and protected areas from the USGS Ecosystems Mission Area plan that expanded the scope of the original 2007 science strategy, to identify the Bureau’s work in ecosystem science over the next decade (Williams et al., 2013). The plan describes a framework that encompasses both basic and applied science and allows the USGS to continue to contribute meaningfully to conservation and management issues related to the Nation’s parks and ecological resources. This framework relies on maintaining long-standing, collaborative relationships with partners in both conducting science and applying scientific results. Here we summarize the major components of the USGS Ecosystems Science Strategy, articulating the vision, goals and strategic approaches, then outlining some of the proposed actions that will ultimately prove useful to those managing parks and protected areas. We end with a discussion on the future of ecosystem science for the USGS and how it can be used to evaluate ecosystem change and the associated consequences to management of our Nation’s natural resources.

The George Wright Forum↗

USGS2013

Surveillance theory applied to virus detection: a case for targeted discovery

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

Future Virology↗

USGS2013

Advances and applications of occupancy models

Summary: The past decade has seen an explosion in the development and application of models aimed at estimating species occurrence and occupancy dynamics while accounting for possible non-detection or species misidentification. We discuss some recent occupancy estimation methods and the biological systems that motivated their development. Collectively, these models offer tremendous flexibility, but simultaneously place added demands on the investigator. Unlike many mark–recapture scenarios, investigators utilizing occupancy models have the ability, and responsibility, to define their sample units (i.e. sites), replicate sampling occasions, time period over which species occurrence is assumed to be static and even the criteria that constitute ‘detection’ of a target species. Subsequent biological inference and interpretation of model parameters depend on these definitions and the ability to meet model assumptions. We demonstrate the relevance of these definitions by highlighting applications from a single biological system (an amphibian–pathogen system) and discuss situations where the use of occupancy models has been criticized. Finally, we use these applications to suggest future research and model development.

Methods in Ecology and Evolution↗

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↗

USGS2013

Estimating occupancy and predicting numbers of gray wolf packs in Montana using hunter surveys

Reliable knowledge of the status and trend of carnivore populations is critical to their conservation and management. Methods for monitoring carnivores, however, are challenging to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost-efficient method for monitoring gray wolf (Canis lupus) populations. Montana Fish, Wildlife and Parks (MFWP) conducts annual telephone surveys of >50,000 deer and elk hunters. We explored how survey data on hunters' sightings of wolves could be used to estimate the occupancy and distribution of wolf packs and predict their abundance in Montana for 2007–2009. We assessed model utility by comparing our predictions to MFWP minimum known number of wolf packs. We minimized false positive detections by identifying a patch as occupied if 2–25 wolves were detected by ≥3 hunters. Overall, estimates of the occupancy and distribution of wolf packs were generally consistent with known distributions. Our predictions of the total area occupied increased from 2007 to 2009 and predicted numbers of wolf packs were approximately 1.34–1.46 times the MFWP minimum counts for each year of the survey. Our results indicate that multi-season occupancy models based on public sightings can be used to monitor populations and changes in the spatial distribution of territorial carnivores across large areas where alternative methods may be limited by personnel, time, accessibility, and budget constraints.

Montana↗

USGS2013

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗

USGS2013

Selecting among competing models of electro-optic, infrared camera system range performance

Range performance is often the key requirement around which electro-optical and infrared camera systems are designed. This work presents an objective framework for evaluating competing range performance models. Model selection based on the Akaike’s Information Criterion (AIC) is presented for the type of data collected during a typical human observer and target identification experiment. These methods are then demonstrated on observer responses to both visible and infrared imagery in which one of three maritime targets was placed at various ranges. We compare the performance of a number of different models, including those appearing previously in the literature. We conclude that our model-based approach offers substantial improvements over the traditional approach to inference, including increased precision and the ability to make predictions for some distances other than the specific set for which experimental trials were conducted.

Optical Engineering↗