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At least 253 records · Page 14Linked to original sources

USGS2007

Porphyry copper deposit tract definition - A global analysis comparing geologic map scales

Geologic maps are a fundamental data source used to define mineral-resource potential tracts for the first step of a mineral resource assessment. Further, it is generally believed that the scale of the geologic map is a critical consideration. Previously published research has demonstrated that the U.S. Geological Survey porphyry tracts identified for the United States, which are based on 1:500,000-scale geology and larger scale data and published at 1:1,000,000 scale, can be approximated using a more generalized 1:2,500,000-scale geologic map. Comparison of the USGS porphyry tracts for the United States with weights-of-evidence models made using a 1:10,000,000-scale geologic map, which was made for petroleum applications, and a 1:35,000,000-scale geologic map, which was created as context for the distribution of porphyry deposits, demonstrates that, again, the USGS US porphyry tracts identified are similar to tracts defined on features from these small scale maps. In fact, the results using the 1:35,000,000-scale map show a slightly higher correlation with the USGS US tract definition, probably because the conceptual context for this small-scale map is more appropriate for porphyry tract definition than either of the other maps. This finding demonstrates that geologic maps are conceptual maps. The map information shown in each map is selected and generalized for the map to display the concepts deemed important for the map maker's purpose. Some geologic maps of small scale prove to be useful for regional mineral-resource tract definition, despite the decrease in spatial accuracy with decreasing scale. The utility of a particular geologic map for a particular application is critically dependent on the alignment of the intention of the map maker with the application. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗

USGS2017

Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

Journal of the American Water Resources Associatio↗

USGS2016

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika ( Ochotona princeps ) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Global Change Biology↗

USGS2022

Estimation of site terms in ground-motion models for California using horizontal-to-vertical spectral ratios from microtremor

The horizontal‐to‐vertical spectral ratios from microtremor (mHVSR) data obtained at 196 seismic stations in California are used to evaluate three alternative microtremor‐based proxies for site amplification for use in ground‐motion models (GMMs): the site fundamental period ( ⁠ f 0 "> f 0 ⁠ ), the period‐dependent amplitude of the mHVSR( T ), and the normalized amplitude of the mHVSR( T ). The alternative parameters are evaluated for the sites with and without measurements of V S 30 "> V S 30 ⁠ . If a V S 30 "> V S 30 measurement is not available for a site, then f 0 "> f 0 has the highest correlation with the site amplification for short periods ( T <1 s) and the normalized amplitude of the mHVSR( T ) has the highest correlation for long periods ( T ≥1 s). If a measurement of the V S 30 "> V S 30 is available for a site, then the normalized amplitude of the mHVSR( T ) has the highest correlation for the site amplification not explained by V S 30 "> V S 30 for all periods. For both cases, the correlations are strongest at the longer periods as mHVSR( T ) measurements excel at providing valuable information for sites with long‐period amplification due to the deeper velocity structure. In particular, for sites with a V S 30 "> V S 30 measurement, the normalized mHVSR( T ) amplitude provides more information about the long‐period site terms than the basin depth currently used in GMMs. Empirical models of the median and standard deviation of the site terms based on the normalized mHVSR( T ) curves are developed for the two cases. These models can be used directly in the ASK14 GMM to modify the median and aleatory standard deviation or they can be used to estimate the site‐specific site term in the context of a partially nonergodic GMM. Including the mHVSR( T ) measurement can have a significant effect on estimates of the ground motion at a site: the range 5%–95% on the observed HVSR( T ) values corresponds to factors of 0.6–1.6 for the median spectral acceleration for periods between 0.5 and 4 s.

California↗

USGS2010

Geophysical investigations at Hidden Dam, Raymond, California — Flow simulations

Numerical flow modeling and analysis of observation-well data at Hidden Dam are carried out to supplement recent geophysical field investigations at the site (Minsley and others, 2010). This work also is complementary to earlier seepage-related studies at Hidden Dam documented by Cedergren (1980a, b). Known seepage areas on the northwest right abutment area of the downstream side of the dam was documented by Cedergren (1980a, b). Subsequent to the 1980 seepage study, a drainage blanket with a sub-drain system was installed to mitigate downstream seepage. Flow net analysis provided by Cedergren (1980a, b) suggests that the primary seepage mechanism involves flow through the dam foundation due to normal reservoir pool elevations, which results in upflow that intersects the ground surface in several areas on the downstream side of the dam. In addition to the reservoir pool elevations and downstream surface topography, flow is also controlled by the existing foundation geology as well as the presence or absence of a horizontal drain in the downstream portion of the dam. The current modeling study is aimed at quantifying how variability in dam and foundation hydrologic properties influences seepage as a function of reservoir stage. Flow modeling is implemented using the COMSOL Multiphysics software package, which solves the partially saturated flow equations in a two-dimensional (2D) cross-section of Hidden Dam that also incorporates true downstream topography. Use of the COMSOL software package provides a more quantitative approach than the flow net analysis by Cedergren (1980a, b), and allows for rapid evaluation of the influence of various parameters such as reservoir level, dam structure and geometry, and hydrogeologic properties of the dam and foundation materials. Historical observation-well data are used to help validate the flow simulations by comparing observed and predicted water levels for a range of reservoir elevations. The flow models are guided by, and discussed in the context of, the geophysical work (Minsley and others, 2010) where appropriate.

California↗

USGS2014

Testing for multiple invasion routes and source populations for the invasive brown treesnake ( Boiga irregularis ) on Guam: implications for pest management

The brown treesnake ( Boiga irregularis ) population on the Pacific island of Guam has reached iconic status as one of the most destructive invasive species of modern times, yet no published works have used genetic data to identify a source population. We used DNA sequence data from multiple genetic markers and coalescent-based phylogenetic methods to place the Guam population within the broader phylogeographic context of B. irregularis across its native range and tested whether patterns of genetic variation on the island are consistent with one or multiple introductions from different source populations. We also modeled a series of demographic scenarios that differed in the effective size and duration of a population bottleneck immediately following the invasion on Guam, and measured the fit of these simulations to the observed data using approximate Bayesian computation. Our results exclude the possibility of serial introductions from different source populations, and instead verify a single origin from the Admiralty Archipelago off the north coast of Papua New Guinea. This finding is consistent with the hypothesis that B. irregularis was accidentally transported to Guam during military relocation efforts at the end of World War II. Demographic model comparisons suggest that multiple snakes were transported to Guam from the source locality, but that fewer than 10 individuals could be responsible for establishing the population. Our results also provide evidence that low genetic diversity stemming from the founder event has not been a hindrance to the ecological success of B. irregularis on Guam, and at the same time offers a unique ‘genetic opening’ to manage snake density using classical biological approaches.

Biological Invasions↗

USGS2014

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis

Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers ( Meles meles ), brushtail possum ( Trichosurus vulpecula ), and white-tailed deer ( Odocoileus virginianus ). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research on M. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis , prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis , white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovis identified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis . Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd factors and cattle farm prevalence is documented.

Michigan↗

USGS2003

Use of the Legal-Institutional Analysis Model to assess hydropower licensing negotiations

In the United States, the Federal Energy Regulatory Commission (FERC) is responsible for issuing or renewing licenses for hydropower projects owned and operated by power companies. During the licensing process, these companies are required to consult with agencies and other parties that are affected by project operating regimes. Typical participants include state and federal fish and wildlife agencies, environmental interest groups, and the FERC. One of the most difficult tasks facing participants is to reach agreement about what kinds of environmental conditions should be placed on license. Researchers at the United States Geological Survey developed a model to analyze the institutional context of natural resource disputes. The Legal-Institutional Analysis Model (LIAM) is a computerized model that allows an analyst to determine the likely behavior of each organization in a conflict. The model also analyzes the types and levels of negotiating power held by each organization. Researchers at the USGS have used the model in several cases involving hydropower license applications. To use the model, they facilitate workshops for stakeholder groups in order to develop a shared understanding of the likely obstacles and opportunities for successful resolution of the issues. This allows a systematic workshop analyses to develop strategies for successful negotiations, because they are able to better understand the negotiation problem and work more effectively with both their allies and their competitors.

Conference Paper↗

USGS2009

Estimation of Leakage Potential of Selected Sites in Interstate and Tri-State Canals Using Geostatistical Analysis of Selected Capacitively Coupled Resistivity Profiles, Western Nebraska, 2004

With increasing demands for reliable water supplies and availability estimates, groundwater flow models often are developed to enhance understanding of surface-water and groundwater systems. Specific hydraulic variables must be known or calibrated for the groundwater-flow model to accurately simulate current or future conditions. Surface geophysical surveys, along with selected test-hole information, can provide an integrated framework for quantifying hydrogeologic conditions within a defined area. In 2004, the U.S. Geological Survey, in cooperation with the North Platte Natural Resources District, performed a surface geophysical survey using a capacitively coupled resistivity technique to map the lithology within the top 8 meters of the near-surface for 110 kilometers of the Interstate and Tri-State Canals in western Nebraska and eastern Wyoming. Assuming that leakage between the surface-water and groundwater systems is affected primarily by the sediment directly underlying the canal bed, leakage potential was estimated from the simple vertical mean of inverse-model resistivity values for depth levels with geometrically increasing layer thickness with depth which resulted in mean-resistivity values biased towards the surface. This method generally produced reliable results, but an improved analysis method was needed to account for situations where confining units, composed of less permeable material, underlie units with greater permeability. In this report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, the authors use geostatistical analysis to develop the minimum-unadjusted method to compute a relative leakage potential based on the minimum resistivity value in a vertical column of the resistivity model. The minimum-unadjusted method considers the effects of homogeneous confining units. The minimum-adjusted method also is developed to incorporate the effect of local lithologic heterogeneity on water transmission. Seven sites with differing geologic contexts were selected following review of the capacitively coupled resistivity data collected in 2004. A reevaluation of these sites using the mean, minimum-unadjusted, and minimum-adjusted methods was performed to compare the different approaches for estimating leakage potential. Five of the seven sites contained underlying confining units, for which the minimum-unadjusted and minimum-adjusted methods accounted for the confining-unit effect. Estimates of overall leakage potential were lower for the minimum-unadjusted and minimum-adjusted methods than those estimated by the mean method. For most sites, the local heterogeneity adjustment procedure of the minimum-adjusted method resulted in slightly larger overall leakage-potential estimates. In contrast to the mean method, the two minimum-based methods allowed the least permeable areas to control the overall vertical permeability of the subsurface. The minimum-adjusted method refined leakage-potential estimation by additionally including local lithologic heterogeneity effects.

Scientific Investigations Report↗

USGS2010

Modeling hexavalent chromium reduction in groundwater in field-scale transport and laboratory batch experiments

A plausible and consistent model is developed to obtain a quantitative description of the gradual disappearance of hexavalent chromium (Cr(VI)) from groundwater in a small-scale field tracer test and in batch kinetic experiments using aquifer sediments under similar chemical conditions. The data exhibit three distinct timescales. Fast reduction occurs in well-stirred batch reactors in times much less than 1 hour and is followed by slow reduction over a timescale of the order of 2 days. In the field, reduction occurs on a timescale of the order of 8 days. The model is based on the following hypotheses. The chemical reduction reaction occurs very fast, and the longer timescales are caused by diffusion resistance. Diffusion into the secondary porosity of grains causes the apparent slow reduction rate in batch experiments. In the model of the field experiments, the reducing agent, heavy Fe(II)-bearing minerals, is heterogeneously distributed in thin strata located between larger nonreducing sand lenses that comprise the bulk of the aquifer solids. It is found that reducing strata of the order of centimeters thick are sufficient to contribute enough diffusion resistance to cause the observed longest timescale in the field. A one-dimensional advection/dispersion model is formulated that describes the major experimental trends. Diffusion rates are estimated in terms of an elementary physical picture of flow through a stratified medium containing identically sized spherical grains. Both reduction and sorption reactions are included. Batch simulation results are sensitive to the fraction of reductant located at or near the surface of grains, which controls the amount of rapid reduction, and the secondary porosity, which controls the rate of slow reduction observed in batch experiments. Results of Cr(VI) transport simulations are sensitive to the thickness and relative size of the reducing stratum. Transport simulation results suggest that nearly all of the reductant must be located in the reducing stratum. Within this context and as long as there is adequate reductive capacity present, the transport simulation results are insensitive to the parameters important for the batch simulations. The results illustrate how a combination of field measurements and batch laboratory studies can be used to improve predictive modeling of contaminant transport.

Water Resources Research↗

USGS2011

A preliminary assessment of the spatial sources of contemporary suspended sediment in the Ohio River basin, United States, using water quality data from the NASQAN programme in a source tracing procedure

Reliable information on catchment scale suspended sediment sources is required to inform the design of management strategies for helping abate the numerous environmental issues associated with enhanced sediment mobilization and off‐site loadings. Since sediment fingerprinting techniques avoid many of the logistical constraints associated with using more traditional indirect measurement methods at catchment scale, such approaches have been increasingly reported in the international literature and typically use data sets collected specifically for sediment source apportionment purposes. There remains scope for investigating the potential for using geochemical data sets assembled by routine monitoring programmes to fingerprint sediment provenance. In the United States, routine water quality samples are collected as part of the US Geological Survey's revised National Stream Quality Accounting Network programme. Accordingly, the geochemistry data generated from these samples over a 10‐year period (1996–2006) were used as the basis for a fingerprinting exercise to assess the key tributary sub‐catchment spatial sources of contemporary suspended sediment transported by the Ohio River. Uncertainty associated with the spatial source estimates was quantified using a Monte Carlo approach in conjunction with mass balance modelling. Relative frequency weighted means were used as an alternative way of summarizing the spatial source contributions, thereby avoiding the need to use confidence limits. The results should be interpreted in the context of the routine, but infrequent nature, of the suspended sediment samples used to assemble geochemistry as a basis for the sourcing exercise. Nonetheless, the study demonstrates how routine monitoring samples can be used to provide some preliminary information on sediment provenance in large drainage basins.

Tennessee, Ohio, West Virginia, Pennsylvania, Indi↗

USGS2018

Modeling golden eagle‐vehicle collisions to design mitigation strategies

The incidental take of golden eagles ( Aquila chrysaetos ) as a result of wind energy development requires some form of compensatory mitigation. Although several options have been proposed, only one has been formerly accepted and implemented, and the lack of options can limit the permit process for wind facilities. We developed a model to estimate numbers of golden eagles that die when struck by vehicles when eagles scavenge road kill to evaluate removal of road‐killed carcasses as an additional mitigation option. Our model estimates vehicle collision rates as a function of eagle densities, road traffic volume, and animal carcass abundance at the scale of a Wyoming, USA, county during fall‐winter, and quantifies the effects of different mitigation strategies, including estimates of uncertainty. We evaluated the plausibility of our model estimates by predicting mortality rates for each county in Wyoming and comparing overall state mortality to current estimates of mortality using derived estimates from expert judgment. We also developed a context‐dependent analysis of potential mitigation credits controlling for carcass number, traffic volume, and background carcass removals. We found that mitigation credit should be highest in areas with greatest number of carcasses. Collision mitigation is a potentially useful addition to the mitigation toolbox for wind energy development or other activities that need to offset predicted golden eagle mortality and satisfy incidental take permit requirements.

Wyoming↗

USGS2023

Recognizing political influences in participatory social-ecological systems modeling

Stakeholder participation in social-ecological systems (SES) modeling is increasingly considered a desirable way to elicit diverse sources of knowledge about SES behavior and to promote inclusive decision-making in SES. Understanding how participatory modeling processes function in the context of long-term adaptive management of SES may allow for better design of participatory processes to achieve the intended outcomes of inclusionary knowledge, representativeness, and social learning, while avoiding unintended outcomes. Long-term adaptive management contexts often include political influences -- attempts to shift or preserve power structures and authority, and efforts to represent the political and economic interests of stakeholders -- in the computer models that are used to shape policy making and implementation. In this research, we examine a period that included a major transition in the watershed model used for management of the Chesapeake Bay in the United States. The Chesapeake Bay watershed model has been in development since the 1980s, and is considered by many to be an exemplary case of participatory modeling. We use documentary analysis and interviews with participants involved in the model application and development transition to reveal a variety of ways in which participatory modeling may be subject to different kinds of political influences, some of which resulted in unintended outcomes, including: perceptions of difficulty updating the model in substantive ways, “gaming” of the model/participatory process by stakeholders, and increasing resistance against considering uncertainty in the system not captured by the model. This research suggests unintended or negative outcomes may be associated with both participatory decision-making and stakeholder learning even though they are so often touted as the benefits of participatory modeling. We end with a hypothesis that further development of a theory of computer model governance to bridge model impact and broader theories of environmental governance at the science-policy interface may result in improved SES modeling outcomes.

Maryland, Virginia↗

USGS2022

Absolute accuracy assessment of lidar point cloud using amorphous objects

The accuracy assessment of airborne lidar point cloud typically estimates vertical accuracy by computing RMSEz (root mean square error of the z coordinate) from ground check points (GCPs). Due to the low point density of the airborne lidar point cloud, there is often not enough accurate semantic context to find an accurate conjugate point. To advance the accuracy assessment in full three-dimensional (3D) context, geometric features, such as the three-plane intersection point or two-line intersection point, are often used. Although the point density is still low, geometric features are mathematically modeled from many points. Thus, geometric features provide a robust determination of the intersection point, and the point is considered as a GCP. When no regular built objects are available, we describe the process of utilizing features of irregular shape called amorphous natural objects, such as a tree or a rock. When scanned to a high-density point cloud, an amorphous natural object can be used as ground truth reference data to estimate 3D georeferencing errors of the airborne lidar point cloud. The algorithm to estimate 3D accuracy is the optimization that minimizes the sum of the distance between the airborne lidar points to the ground scanned data. The search volume partitioning was the most important procedure to improve the computational efficiency. We also performed an extensive study to address the external uncertainty associated with the amorphous object method. We describe an accuracy assessment using amorphous objects (108 trees) spread over the project area. The accuracy results for ∆ x , ∆ y , and ∆ z obtained using the amorphous object method were 3.1 cm, 3.6 cm, and 1.7 cm RMSE, along with a mean error of 0.1 cm, 0.1 cm, and 4.5 cm, respectively, satisfying the accuracy requirement of U.S. Geological Survey lidar base specification. This approach shows strong promise as an alternative to geometric feature methods when artificial targets are scarce. The relative convenience and advantages of using amorphous targets, along with its good performance shown here, make this amorphous object method a practical way to perform 3D accuracy assessment.

Remote Sensing↗

USGS2014

Managing harvest and habitat as integrated components

In 2007, several important initiatives in the North American waterfowl management community called for an integrated approach to habitat and harvest management. The essence of the call for integration is that harvest and habitat management affect the same resources, yet exist as separate endeavours with very different regulatory contexts. A common modelling framework could help these management streams to better understand their mutual effects. Particularly, how does successful habitat management increase harvest potential? Also, how do regional habitat programmes and large-scale harvest strategies affect continental population sizes (a metric used to express habitat goals)? In the ensuing five years, several projects took on different aspects of these challenges. While all of these projects are still on-going, and are not yet sufficiently developed to produce guidance for management decisions, they have been influential in expanding the dialogue and producing some important emerging lessons. The first lesson has been that one of the more difficult aspects of integration is not the integration across decision contexts, but the integration across spatial and temporal scales. Habitat management occurs at local and regional scales. Harvest management decisions are made at a continental scale. How do these actions, taken at different scales, combine to influence waterfowl population dynamics at all scales? The second lesson has been that consideration of the interface of habitat and harvest management can generate important insights into the objectives underlying the decision context. Often the objectives are very complex and trade-off against one another. The third lesson follows from the second – if an understanding of the fundamental objectives is paramount, there is no escaping the need for a better understanding of human dimensions, specifically the desires of hunters and nonhunters and the role they play in conservation. In the end, the compelling question is how to better understand, guide and justify decisions about conservation investments in waterfowl management. Future efforts to integrate harvest and habitat management will include completion of the species-specific case-studies, initiation of policy discussions around how to integrate the decision contexts and governing institutions, and possible consideration of a new level of integration – integration of harvest and habitats management decisions across waterfowl stocks.

Wildfowl↗

USGS2024

Exploring and integrating differences in niche characteristics across regional and global scales to better understand plant invasions in Hawaiʻi

The spread of ecosystem modifying invasive plant (EMIP) species is one of the largest threats to native ecosystems in Hawaiʻi. However, differences in niche characteristics between Hawaiʻi’s isolated insular environment and the wider global distribution of these species have not been carefully examined. We used species distribution modeling (SDM) methods to assess similarities and differences in niche characteristics between global and regional scales for 17 EMIPs present in Hawaiʻi. With a clearer understanding of the global context of regional plant invasion, we combined two SDM methods to better understand the potential future regional spread: (1) a nested modeling approach to integrate global and regional invasive species distribution projections; and (2) integrating all available agency and citizen science data to minimize the effect of monitoring gaps and biases. Our results show there are multiple similarities in niche characteristics across regional and global scales for most species, such as similar sets of climatic determinants of distribution, similar responses along environmental gradients, and moderate to high niche overlap between global and regional models. However, some differences were apparent and likely due to several factors including incomplete regional spread, community assembly or diversity effects. Invaders that established earlier showed a higher degree of niche overlap and similar environmental gradient responses when comparing global and regional models. This pattern, coupled with the tendency for regionally-based projections to predict narrower distributions than global projections, indicates a potential for continued spread of several invasive species across the Hawaiian landscape. Our study has broader implications for understanding the distribution and spread of invasive species in other regions, as similar analyses and models, including a novel way to characterize environmental gradient response differences across regions or scales, can likely provide valuable information for conservation and management efforts.

Hawaii↗

USGS2004

Estimation of sex-specific survival from capture-recapture data when sex is not always known

Many animals lack obvious sexual dimorphism, making assignment of sex difficult even for observed or captured animals. For many such species it is possible to assign sex with certainty only at some occasions; for example, when they exhibit certain types of behavior. A common approach to handling this situation in capture-recapture studies has been to group capture histories into those of animals eventually identified as male and female and those for which sex was never known. Because group membership is dependent on the number of occasions at which an animal was caught or observed (known sex animals, on average, will have been observed at more occasions than unknown-sex animals), survival estimates for known-sex animals will be positively biased, and those for unknown animals will be negatively biased. In this paper, we develop capture-recapture models that incorporate sex ratio and sex assignment parameters that permit unbiased estimation in the face of this sampling problem. We demonstrate the magnitude of bias in the traditional capture-recapture approach to this sampling problem, and we explore properties of estimators from other ad hoc approaches. The model is then applied to capture-recapture data for adult Roseate Terns ( Sterna dougallii ) at Falkner Island, Connecticut, 1993-2002. Sex ratio among adults in this population favors females, and we tested the hypothesis that this population showed sex-specific differences in adult survival. Evidence was provided for higher survival of adult females than males, as predicted. We recommend use of this modeling approach for future capture-recapture studies in which sex cannot always be assigned to captured or observed animals. We also place this problem in the more general context of uncertainty in state classification in multistate capture-recapture models.

Connecticut↗

USGS2016

An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.

Journal of Hydrology↗