Abundance is the state variable of interest in most population–level ecological research and in most programs involving management and conservation of animal populations. Abundance is the single parameter of interest in capture–recapture models for closed populations (e.g., Darroch, 1958; Otis et al., 1978; Chao, 2001). The initial capture–recapture models developed for partially (Darroch, 1959) and completely (Jolly, 1965; Seber, 1965) open populations represented efforts to relax the restrictive assumption of population closure for the purpose of estimating abundance. Subsequent emphases in capture–recapture work were on survival rate estimation in the 1970’s and 1980’s (e.g., Burnham et al., 1987; Lebreton et al.,1992), and on movement estimation in the 1990’s (Brownie et al., 1993; Schwarz et al., 1993). However, from the mid–1990’s until the present time, capture–recapture investigators have expressed a renewed interest in abundance and related parameters (Pradel, 1996; Schwarz & Arnason, 1996; Schwarz, 2001). The focus of this session was abundance, and presentations covered topics ranging from estimation of abundance and rate of change in abundance, to inferences about the demographic processes underlying changes in abundance, to occupancy as a surrogate of abundance. The plenary paper by Link & Barker (2004) is provocative and very interesting, and it contains a number of important messages and suggestions. Link & Barker (2004) emphasize that the increasing complexity of capture–recapture models has resulted in large numbers of parameters and that a challenge to ecologists is to extract ecological signals from this complexity. They offer hierarchical models as a natural approach to inference in which traditional parameters are viewed as realizations of stochastic processes. These processes are governed by hyperparameters, and the inferential approach focuses on these hyperparameters. Link & Barker (2004) also suggest that our attention should be focused on relationships between demographic processes such as survival and recruitment, the two quantities responsible for changes in abundance, rather than simply on the magnitudes of these quantities. They describe a type of Jolly–Seber capture–recapture model that permits inference about the underlying relationship between per capita recruitment rates and survival rates (Link & Barker, this volume). Implementation used Bayesian Markov Chain Monte Carlo methods and appeared to work well, yielding inferences about the relationship between recruitment and survival that were robust to selection of prior distribution. We believe that readers will find their arguments compelling, and we expect to see increased use of hierarchical modeling approaches in capture–recapture and related fields. Otto (presentation without paper) also recommended use of hierarchical models in analysis of multiple data sources dealing with population dynamics of North American mallards. He integrated survival inferences from ringing data, abundance information from aerial survey data, and recruitment information based on age ratios from a harvest survey. He used a Leslie matrix population projection model as an integrating framework and obtained estimates of breeding population size using all data.Otto’s approach also permitted inference about biases in estimated quantities. As with the work of Link & Barker (2004), we find Otto’s recommendation to use hierarchical models to integrate data from multiple sources to be very compelling. Alisauskas et al. (2004) report results of an analysis of capture–recapture data for a askatchewan population of white–winged scoters. They used the approach of Pradel (1996) to estimate population growth rate (See the PDF) directly. Estimates for 1975–1985 were quite low, but estimates for the recent period, 2000–2003,increased to values > 1. Parameter estimates for seniority, survival and per capita recruitment (Pradel, 1996) led to the inference that increased recruitment was largely responsible for the improvements in population status and growth. However, various data sources also indicated that this increase in recruitment was likely a result of increased immigration rather than improved reproduction on the area. This latter inference is important from a conservation perspective in indicating the importance of birds in other locations to growth and health of the study population. Lukacs and Burnham presented material to be published elsewhere that dealt with the use of genetic markers in capture–recapture studies. The data sources for such studies are samples of hair or feces, which are then analyzed using molecular genetic techniques in order to determine individual genotypes with respect to a usually small number of loci. Two types of classification error can arise in such analyses. First, if only a small number of loci is examined, then there may be nonnegligible probabilities that multiple individual animals will have the same genotypes. The second type of error arises during the polymerase chain reaction (PCR) process and can result from failure of alleles to amplify (allelic dropout) or from PCR inhibitors in hair and feces that produce the appearance of false alleles or misprinting (Creel et al., 2003). Lukacs and Burnham developed models that formally incorporate possible misclassification of samples resulting from these errors. These models permit estimation of parameters such as abundance and survival in a manner that properly incorporates this uncertainty of individual identity. We anticipate that noninvasive sampling based on molecular genetic analyses of hair or feces will become extremely important for some species, and that the models of Lukacs and Burnham will become very popular for such analyses. MacKenzie & Nichols (2004) discuss the use of occupancy (proportion of patches or habitat area that is occupied) as a surrogate for abundance. In cases of territorial species and where birds occur at low densities, the number of occupied patches may provide a reasonable estimate of abundance. In other cases, occupancy can be viewed as providing information about one tail of the abundance distribution, P (N = 0). The motivation for considering occupancy as a surrogate for abundance is that occupancy is based on so–called presence–absence surveys that are frequently less expensive of time and effort than methods that estimate abundance directly. We describe one set of models that can be used to estimate occupancy for a single season and another that can be used to estimate parameters such as local probabilities of extinction and colonization that are associated with occupancy dynamics. We outline a possible hybrid approach that combines occupancy data with data on marked individuals in order to betterexplore the mechanisms underlying occupancy dynamics. These five presentations made for an interesting session containing useful information and recommendations for future work. A number of themes connecting these presentations could be emphasized. For example, two of the presentations considered alternatives to standard capture–recapture sampling that can be used to draw inferences about abundance, or a portion of the abundance distribution, with field methods that should be less expensive than usual capture–recapture approaches of handling animals. We believe that the most important theme of the session was the emphasis on the processes responsible for changes in abundance. In particular, we are excited by the potential for using hierarchical models as a means of investigating relationships among vital rates and as a means of combining multiple sources of data relevant to system dynamics. Indeed, we expect the importance of this session theme to be reflected in the content and presentations of the next EURING meeting.
","language":"English","publisher":"Museu de Ciencies Naturals de Barcelona","usgsCitation":"Nichols, J., and MacKenzie, D., 2004, Abundance estimation and conservation biology: Animal Biodiversity and Conservation, v. 27, no. 1, p. 437-439.","productDescription":"3 p.","startPage":"437","endPage":"439","numberOfPages":"3","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":196327,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":16752,"rank":300,"type":{"id":15,"text":"Index Page"},"url":"https://abc.museucienciesjournals.cat/volum-27-1-2004-abc/abundance-estimation-and-conservation-biology/?lang=en","linkFileType":{"id":5,"text":"html"}}],"volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b13e4b07f02db6a3808","contributors":{"authors":[{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":341668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacKenzie, D.I.","contributorId":69522,"corporation":false,"usgs":true,"family":"MacKenzie","given":"D.I.","email":"","affiliations":[],"preferred":false,"id":341669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5224436,"text":"5224436 - 2004 - Hierarchial mark-recapture models: a framework for inference about demographic processes","interactions":[],"lastModifiedDate":"2016-10-27T12:05:09","indexId":"5224436","displayToPublicDate":"2010-06-16T12:18:29","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":771,"text":"Animal Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchial mark-recapture models: a framework for inference about demographic processes","docAbstract":"The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.
","language":"English","publisher":"Museu de Ciencies Natural de Barcelona","usgsCitation":"Link, W., and Barker, R.J., 2004, Hierarchial mark-recapture models: a framework for inference about demographic processes: Animal Biodiversity and Conservation, v. 27, no. 1, p. 441-449.","productDescription":"9 p.","startPage":"441","endPage":"449","numberOfPages":"9","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202029,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":16753,"rank":300,"type":{"id":15,"text":"Index Page"},"url":"https://abc.museucienciesjournals.cat/volum-27-1-2004-abc/hierarchial-mark-recapture-models-a-framework-for-inference-about-demographic-processes/?lang=en","linkFileType":{"id":5,"text":"html"}}],"volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db635b44","contributors":{"authors":[{"text":"Link, W.A. 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":8815,"corporation":false,"usgs":true,"family":"Link","given":"W.A.","affiliations":[],"preferred":false,"id":341670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barker, R. J.","contributorId":34222,"corporation":false,"usgs":false,"family":"Barker","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":341671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5224434,"text":"5224434 - 2004 - Generalized estimators of avian abundance from count survey data","interactions":[],"lastModifiedDate":"2016-10-27T12:08:11","indexId":"5224434","displayToPublicDate":"2010-06-16T12:18:29","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":771,"text":"Animal Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Generalized estimators of avian abundance from count survey data","docAbstract":"I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.","language":"English","publisher":"Museu de Ciencies Naturals de Barcelona","usgsCitation":"Royle, J., 2004, Generalized estimators of avian abundance from count survey data: Animal Biodiversity and Conservation, v. 27, no. 1, p. 375-386.","productDescription":"12 p.","startPage":"375","endPage":"386","numberOfPages":"12","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":196077,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":16751,"rank":300,"type":{"id":15,"text":"Index Page"},"url":"https://abc.museucienciesjournals.cat/volum-27-1-2004-abc/generalized-estimators-of-avian-abundance-from-count-survey-data/?lang=en","linkFileType":{"id":5,"text":"html"}}],"volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b26e4b07f02db6afca2","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":96221,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[],"preferred":false,"id":341667,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":5224430,"text":"5224430 - 2004 - Computing and software","interactions":[],"lastModifiedDate":"2016-10-27T12:02:10","indexId":"5224430","displayToPublicDate":"2010-06-16T12:18:29","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":771,"text":"Animal Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Computing and software","docAbstract":"The reality is that the statistical methods used for analysis of data depend upon the availability of software. Analysis of marked animal data is no different than the rest of the statistical field. The methods used for analysis are those that are available in reliable software packages. Thus, the critical importance of having reliable, up–to–date software available to biologists is obvious. Statisticians have continued to develop more robust models, ever expanding the suite of potential analysis methods
available. But without software to implement these newer methods, they will languish in the abstract, and not be applied to the problems deserving them.
In the Computers and Software Session, two new software packages are described, a comparison of implementation of methods for the estimation of nest survival is provided, and a more speculative paper about how the next generation of software might be structured is presented.
Rotella et al. (2004) compare nest survival estimation with different software packages: SAS logistic regression, SAS non–linear mixed models, and Program MARK. Nests are assumed to be visited at various, possibly infrequent, intervals. All of the approaches described compute nest survival with the same likelihood, and require that the age of the nest is known to account for nests that eventually hatch. However, each approach offers advantages and disadvantages, explored by Rotella et al. (2004).
Efford et al. (2004) present a new software package called DENSITY. The package computes population abundance and density from trapping arrays and other detection methods with a new and unique approach. DENSITY represents the first major addition to the analysis of trapping arrays in 20 years.
Barker & White (2004) discuss how existing software such as Program MARK require that each new model’s likelihood must be programmed specifically for that model. They wishfully think that future software might allow the user to combine pieces of likelihood functions together to generate estimates. The idea is interesting, and maybe some bright young statistician can work out the specifics to implement the procedure.
Choquet et al. (2004) describe MSURGE, a software package that implements the multistate capture–recapture models. The unique feature of MSURGE is that the design matrix is constructed with an interpreted language called GEMACO. Because MSURGE is limited to just multistate models, the special requirements of these likelihoods can be provided.
The software and methods presented in these papers gives biologists and wildlife managers an expanding range of possibilities for data analysis. Although ease–of–use is generally getting better, it does not replace the need for understanding of the requirements and structure of the models being computed. The internet provides access to many free software packages as well as user–discussion groups to share knowledge and ideas. (A starting point for wildlife–related applications is (http://www.phidot.org).
The Chesapeake Bay osprey population has more than doubled in size since restrictions were placed on the production and use of DDT and other toxic organochlorine contaminants in the 1970s. Ospreys are now nesting in the most highly polluted portions of the Bay. In 2000 and 2001, contaminant exposure and reproduction were monitored in ospreys nesting in regions of concern, including Baltimore Harbor and the Patapsco River, the Anacostia and middle Potomac rivers, and the Elizabeth River, and a presumed reference site consisting of the South, West, and Rhode rivers. A 'sample egg' from each study nest was collected for contaminant analysis, and the fate of eggs remaining in each nest (n = 14-16/site) was monitored at 7- to 10-day intervals from egg incubation through fledging of young. Ospreys fledged young in regions of concern (observed success: 0.88 -1.53 fledglings/active nest), although productivity was marginal for sustaining local populations in Baltimore Harbor and the Patapsco River and in the Anacostia and middle Potomac rivers. Concentrations of p,p'DDE and many other organochlorine pesticides or metabolites, total PCBs, some arylhydrocarbon receptor-active PCB congeners and polybrominated diphenyl ether congeners, and perfluorooctanesulfonate were often greater in sample eggs from regions of concern compared to the reference site. Nonetheless, logistic regression analyses did not provide evidence linking marginal productivity to p,p' -DDE, total PCBs, or arylhydrocarbon receptor-active PCB congener exposure in regions of concern. In view of the moderate concentrations of total PCBs in eggs from the reference site, concerns related to new and emerging toxicants, and the absence of ecotoxicological data for terrestrial vertebrates in many Bay tributaries, a more thorough spatial evaluation of contaminant exposure in ospreys throughout the Chesapeake may be warranted.
","language":"English","publisher":"Springer","doi":"10.1007/s00244-003-3160-0","usgsCitation":"Rattner, B., McGowan, P.C., Golden, N.H., Hatfield, J., Toschik, P.C., Lukei, R., Hale, R., Schmitz-Afonso, I., and Rice, C., 2004, Contaminant exposure and reproductive success of Ospreys (Pandion haliaetus) nesting in Chesapeake Bay regions of concern: Archives of Environmental Contamination and Toxicology, v. 47, no. 1, p. 126-140, https://doi.org/10.1007/s00244-003-3160-0.","productDescription":"15 p.","startPage":"126","endPage":"140","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201508,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db697216","contributors":{"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":95843,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett A.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":341224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, P. C.","contributorId":67191,"corporation":false,"usgs":false,"family":"McGowan","given":"P.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":341222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, N. H.","contributorId":55541,"corporation":false,"usgs":true,"family":"Golden","given":"N.","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":341220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Jeff S.","contributorId":41372,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeff S.","affiliations":[],"preferred":false,"id":341219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toschik, P. C.","contributorId":18879,"corporation":false,"usgs":true,"family":"Toschik","given":"P.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":341217,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lukei, R.F. Jr.","contributorId":39909,"corporation":false,"usgs":true,"family":"Lukei","given":"R.F.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":341218,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hale, R. C.","contributorId":11309,"corporation":false,"usgs":true,"family":"Hale","given":"R. C.","affiliations":[],"preferred":false,"id":341216,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schmitz-Afonso, I.","contributorId":61134,"corporation":false,"usgs":true,"family":"Schmitz-Afonso","given":"I.","email":"","affiliations":[],"preferred":false,"id":341221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rice, C.P.","contributorId":81065,"corporation":false,"usgs":true,"family":"Rice","given":"C.P.","email":"","affiliations":[],"preferred":false,"id":341223,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":5221159,"text":"5221159 - 2004 - Assessing the fit of site-occupancy models","interactions":[],"lastModifiedDate":"2021-08-30T15:31:31.262398","indexId":"5221159","displayToPublicDate":"2010-06-16T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the fit of site-occupancy models","docAbstract":"Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.
","language":"English","publisher":"SpringerLink","doi":"10.1198/108571104X3361","usgsCitation":"MacKenzie, D., and Bailey, L., 2004, Assessing the fit of site-occupancy models: Journal of Agricultural, Biological, and Environmental Statistics, v. 9, no. 3, p. 300-318, https://doi.org/10.1198/108571104X3361.","productDescription":"19 p.","startPage":"300","endPage":"318","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":193984,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.968505859375,\n 35.29943548054545\n ],\n [\n -83.0126953125,\n 35.29943548054545\n ],\n [\n -83.0126953125,\n 35.746512259918504\n ],\n [\n -83.968505859375,\n 35.746512259918504\n ],\n [\n -83.968505859375,\n 35.29943548054545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db672a37","contributors":{"authors":[{"text":"MacKenzie, D.I.","contributorId":69522,"corporation":false,"usgs":true,"family":"MacKenzie","given":"D.I.","email":"","affiliations":[],"preferred":false,"id":333160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, L.L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":61006,"corporation":false,"usgs":true,"family":"Bailey","given":"L.L.","affiliations":[],"preferred":false,"id":333159,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5200286,"text":"5200286 - 2004 - Mute swans and their Chesapeake Bay habitats: proceedings of a symposium","interactions":[],"lastModifiedDate":"2022-04-15T13:25:23.651773","indexId":"5200286","displayToPublicDate":"2009-06-09T10:33:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":37,"text":"Information and Technology Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2004-0005.","title":"Mute swans and their Chesapeake Bay habitats: proceedings of a symposium","docAbstract":"The symposium 'Mute Swans and their Chesapeake Bay Habitats,' held on June 7, 2001, provided a forum for biologists and managers to share research findings and management ideas concerning the exotic and invasive mute swan (Cygnus olar). This species has been increasing in population size and is considered by many to be a problem in regard to natural food resources in the Bay that are used by native waterfowl during the winter months. Other persons, however, feel that resource managers are attempting to create a problem to justify more killing of waterfowl by hunters. Some persons also believe that managers should focus on the larger issues causing the decline of native food resources, such as the unabated human population increase in the Bay watershed and in the immediate coastal areas of the Bay. The symposium, sponsored by the Wildfowl Trust of North America and the U.S. Geological Survey, provided the atmosphere for presentation of mute swan data and opinions in a collegial setting where discussion was welcomed and was often informative and enthusiastic. An interesting historic review of the swan in regard to the history of mankind was presented, followed by a discussion on the positive and negative effects of invasive species. Biologists from different parts of the continent discussed the population status of the species in several states in the east and in the Great Lakes area. Data on the food habits of this species were presented in regard to submerged aquatic vegetation, and an interesting discussion on the role that the food habits of Canada geese in regard to native vegetation was presented. Findings and recommendations of the Mute Swan Task Force were presented. Finally, a representative of the Friends of Animals gave a thought-provoking presentation in defense of the mute swan. The presentations, in general, provided the necessary information and recommendations to allow managers to proceed with management of this controversial species with new and valuable perspectives.","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","usgsCitation":"2004, Mute swans and their Chesapeake Bay habitats: proceedings of a symposium: Information and Technology Report 2004-0005., vii, 59.","productDescription":"vii, 59","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201079,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.11328125,\n 36.94111143010769\n ],\n [\n -75.992431640625,\n 37.155938651244625\n ],\n [\n -75.87158203125,\n 37.53586597792038\n ],\n [\n -75.640869140625,\n 37.95286091815649\n ],\n [\n -75.87158203125,\n 37.98750437106374\n ],\n [\n -75.772705078125,\n 38.12159327165922\n ],\n [\n -75.8551025390625,\n 38.406253794852674\n ],\n [\n -76.09130859375,\n 39.05758374935667\n ],\n [\n -75.860595703125,\n 39.57605638518604\n ],\n [\n -75.9539794921875,\n 39.614152077002664\n ],\n [\n -76.2890625,\n 39.48284540453334\n ],\n [\n -76.717529296875,\n 39.23650795487107\n ],\n [\n -76.61865234374999,\n 38.50519140240356\n ],\n [\n -77.05810546875,\n 38.371808917147554\n ],\n [\n -77.05810546875,\n 38.182068998322094\n ],\n [\n -76.57470703125,\n 37.38761749978395\n ],\n [\n -76.5966796875,\n 37.23470197166817\n ],\n [\n -76.47033691406249,\n 36.86643755175846\n ],\n [\n -76.11328125,\n 36.94111143010769\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b02e4b07f02db698a02","contributors":{"editors":[{"text":"Perry, Matthew C. 0000-0001-6452-9534","orcid":"https://orcid.org/0000-0001-6452-9534","contributorId":16372,"corporation":false,"usgs":true,"family":"Perry","given":"Matthew C.","affiliations":[],"preferred":false,"id":505867,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":5200282,"text":"5200282 - 2004 - Population dynamics of the California Spotted Owl (Strix occidentalis occidentalis): a meta-analysis","interactions":[],"lastModifiedDate":"2012-02-02T00:15:27","indexId":"5200282","displayToPublicDate":"2009-06-09T09:33:22","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":203,"text":"Ornithological Monographs","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"No. 54.","title":"Population dynamics of the California Spotted Owl (Strix occidentalis occidentalis): a meta-analysis","docAbstract":"We conducted a meta-analysis to provide a current assessment of the population characteristics of California Spotted Owls (Strix occidentalis occidentalis) resident on four study areas in the Sierra Nevada and one study area in southern California. Our meta-analysis followed rigorous a priori analysis protocols, which we derived through extensive discussion during a week-long analysis workshop. Because there is great interest in the owl?s population status, we used state-of-the-art analytical methods to obtain results as precise as possible. Our meta-analysis included data from five California study areas located on the Lassen National Forest (1990-2000), Eldorado National Forest (1986-2000), Sierra National Forest (1990-2000), Sequoia and Kings Canyon national parks (1990-2000), and San Bernardino National Forest (1987-1998). Four of the five study areas spanned the length of the Sierra Nevada, whereas the fifth study area encompassed the San Bernardino Mountains in southern California. Study areas ranged in size from 343 km2 (Sequoia and Kings Canyon) to 2,200 km (Lassen). All studies were designed to use capture-recapture methods and analysis. We used survival in a meta-analysis because field methods were very similar among studies. However, we did not use reproduction in a meta-analysis because it was not clear if variation among individual study-area protocols used to assess reproductive output of owls would confound results. Thus, we analyzed fecundity only by individual study area. We examined population trend using the reparameterized Jolly-Seber capture-recapture estimator (8t) We did not estimate juvenile survival rates because of estimation problems and potential bias because of juvenile emigration from study areas. We used mark-recapture estimators under an information theoretic framework to assess apparent survival rates of adult owls. The pooled estimate for adult apparent survival for the five study areas was 0.833, which was lower than pooled adult survival rates (0.850) from 15 Northern Spotted Owl (S. o. caurina) studies. Estimates of survival from the best model on the Lassen (N = 0.829, 95% confidence intervals [CI = 0.798 to 0.857), Eldorado (N = 0.815, 95% CI = 0.772 to 0.851), Sierra (N = 0.818, 95% CI = 0.781 to 0.850), and San Bernardino (N = 0.813, 95% CI = 0.782 to 0.841) were not different. However, the Sequoia and Kings Canyon population had a higher survival rate (N = 0.877, 95% CI = 0.842 to 0.905) than the other study areas. Management history and forest structure (e.g. presence of giant sequoia [Sequoiadendron giganteum]) on the Sequoia and Kings Canyon study area differed from all other study areas. There appears to be little or no evidence for temporal variation in adult apparent survival on any of the study areas. Although we did not directly compare fecundity estimates were highly variable among years within all study areas (CV of temporal process variation = 0.672-0.817). Estimates for fecundity among the study populations were Lassen (b = 0.336, SE = 0.083), Eldorado (b = 0.409, SE = 0.087), Sierra (b = 0.284, SE = 0.073), Sequoia and Kings Canyon (b = 0.289, SE = 0.074), and San Bernardino (b = 0.362, SE = 0.038). During most years, the Sierra Nevada populations showed either moderate or poor fecundity. However, 1992 appeared to be an exceptional reproductive year for owls in the Sierra Nevada. In contrast, the San Bernardino population had less variable reproduction (CV of temporal process variation = 0.217), but experienced neither the exceptional reproduction of 1992 nor the extremely poor years that characterized all of the Sierra Nevada study areas. Because fecundity may be influenced by weather patterns, it was possible that the different weather patterns between southern California and the Sierra Nevada accounted for that difference. Except for Eldorado, all estimates for 8t, were <1.0, but none was different from 8 = 1.0 given the 95% confidence i","language":"English","collaboration":" PDF on file: 6132_Franklin.pdf","usgsCitation":"Franklin, A., Gutierrez, R.J., Nichols, J., Seamans, M., White, G.C., Zimmerman, G., Hines, J., Munton, T., LaHaye, W., Blakesley, J., Steger, G., Noon, B., Shaw, D., Keane, J., McDonald, T.L., and Britting, S., 2004, Population dynamics of the California Spotted Owl (Strix occidentalis occidentalis): a meta-analysis: Ornithological Monographs No. 54., 54.","productDescription":"54","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202683,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad6e4b07f02db683f58","contributors":{"authors":[{"text":"Franklin, A.B.","contributorId":105667,"corporation":false,"usgs":true,"family":"Franklin","given":"A.B.","email":"","affiliations":[],"preferred":false,"id":327412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gutierrez, R. J.","contributorId":7647,"corporation":false,"usgs":false,"family":"Gutierrez","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":327397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":327398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seamans, M.E.","contributorId":48662,"corporation":false,"usgs":true,"family":"Seamans","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":327405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Gary C.","contributorId":26256,"corporation":false,"usgs":true,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":327402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, G.S.","contributorId":16126,"corporation":false,"usgs":true,"family":"Zimmerman","given":"G.S.","email":"","affiliations":[],"preferred":false,"id":327399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hines, J.E. 0000-0001-5478-7230","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":36885,"corporation":false,"usgs":true,"family":"Hines","given":"J.E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":327404,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munton, T.E.","contributorId":18884,"corporation":false,"usgs":true,"family":"Munton","given":"T.E.","email":"","affiliations":[],"preferred":false,"id":327400,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"LaHaye, W.S.","contributorId":98854,"corporation":false,"usgs":true,"family":"LaHaye","given":"W.S.","email":"","affiliations":[],"preferred":false,"id":327410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Blakesley, J.A.","contributorId":63920,"corporation":false,"usgs":true,"family":"Blakesley","given":"J.A.","affiliations":[],"preferred":false,"id":327407,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Steger, G.N.","contributorId":92397,"corporation":false,"usgs":true,"family":"Steger","given":"G.N.","email":"","affiliations":[],"preferred":false,"id":327409,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Noon, B.R.","contributorId":24311,"corporation":false,"usgs":true,"family":"Noon","given":"B.R.","email":"","affiliations":[],"preferred":false,"id":327401,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shaw, D.W.H.","contributorId":57577,"corporation":false,"usgs":true,"family":"Shaw","given":"D.W.H.","email":"","affiliations":[],"preferred":false,"id":327406,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Keane, J.J.","contributorId":30729,"corporation":false,"usgs":true,"family":"Keane","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":327403,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McDonald, T. L.","contributorId":101211,"corporation":false,"usgs":false,"family":"McDonald","given":"T.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":327411,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Britting, S.","contributorId":77638,"corporation":false,"usgs":true,"family":"Britting","given":"S.","email":"","affiliations":[],"preferred":false,"id":327408,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":5211265,"text":"5211265 - 2004 - Modeling survival and movement of resident giant Canada goose populations in the Atlantic flyway","interactions":[],"lastModifiedDate":"2012-02-02T00:15:24","indexId":"5211265","displayToPublicDate":"2009-06-09T09:23:19","publicationYear":"2004","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Modeling survival and movement of resident giant Canada goose populations in the Atlantic flyway","docAbstract":"Distribution of resident giant Canada geese (Branta canadensis maxima) has changed markedly in the Atlantic Flyway in recent decades. This change may be related to habitat variation or to changes in hunting regulations. We attempt to assess impacts of hunting regulations on survival, movement, and harvest rate of Canada goose populations from Maine to South Carolina. During 15 June-31 July 1991-1995, a total of 20,923 Canada geese were individually marked with unique metal leg bands and rubber neck collars. Capture-recapture, resighting, and recovery data will be used in a multi-state model of Canada goose populations in New England, the Mid-Atlantic, the Chesapeake Region, and the Carolinas. We plan to model annual survival, movement, and harvest rate as a function of harvest regulations while controlling for collar loss. Inferences will be drawn about the effects of harvest regulations on these parameters. Such inferences should be useful in management of resident Canada goose populations throughout the eastern United States.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2003 International Canada Goose Symposium: papers, abstracts, and posters from the Symposium held in Madison, Wisconsin, 19-21 March 2003","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisherLocation":"Madison, Wisconsin","usgsCitation":"Miller, M., Kendall, W., and Hestbeck, J., 2004, Modeling survival and movement of resident giant Canada goose populations in the Atlantic flyway, chap. of Proceedings of the 2003 International Canada Goose Symposium: papers, abstracts, and posters from the Symposium held in Madison, Wisconsin, 19-21 March 2003.","productDescription":"xvii, 265","startPage":"200 [abstr","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203116,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db6997ce","contributors":{"editors":[{"text":"Moser, Timothy J.","contributorId":112864,"corporation":false,"usgs":true,"family":"Moser","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":507903,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lien, Ricky D.","contributorId":112385,"corporation":false,"usgs":true,"family":"Lien","given":"Ricky","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":507902,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"VerCauterren, Kurt C.","contributorId":113875,"corporation":false,"usgs":true,"family":"VerCauterren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":507904,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Abraham, Kenneth F.","contributorId":32215,"corporation":false,"usgs":true,"family":"Abraham","given":"Kenneth F.","affiliations":[],"preferred":false,"id":507897,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":507896,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Bruggink, John G.","contributorId":34990,"corporation":false,"usgs":true,"family":"Bruggink","given":"John G.","affiliations":[],"preferred":false,"id":507898,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":507900,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Graber, David A.","contributorId":114127,"corporation":false,"usgs":true,"family":"Graber","given":"David A.","affiliations":[],"preferred":false,"id":507905,"contributorType":{"id":2,"text":"Editors"},"rank":8},{"text":"Leafloor, James O.","contributorId":111512,"corporation":false,"usgs":true,"family":"Leafloor","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":507901,"contributorType":{"id":2,"text":"Editors"},"rank":9},{"text":"Luukkonen, David R.","contributorId":111336,"corporation":false,"usgs":true,"family":"Luukkonen","given":"David R.","affiliations":[],"preferred":false,"id":507899,"contributorType":{"id":2,"text":"Editors"},"rank":10},{"text":"Trost, Robert E.","contributorId":114181,"corporation":false,"usgs":true,"family":"Trost","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":507906,"contributorType":{"id":2,"text":"Editors"},"rank":11}],"authors":[{"text":"Miller, M.W.","contributorId":57012,"corporation":false,"usgs":true,"family":"Miller","given":"M.W.","email":"","affiliations":[],"preferred":false,"id":330546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":330545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hestbeck, J.B.","contributorId":107802,"corporation":false,"usgs":true,"family":"Hestbeck","given":"J.B.","affiliations":[],"preferred":false,"id":330547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":5211263,"text":"5211263 - 2004 - On the use of capture-recapture models in mist-net studies","interactions":[],"lastModifiedDate":"2017-03-14T14:49:16","indexId":"5211263","displayToPublicDate":"2009-06-09T09:23:19","publicationYear":"2004","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"29","title":"On the use of capture-recapture models in mist-net studies","docAbstract":"Capture-recapture models provide a statistical framework for estimating population parameters from mist-net data. Although Cormack-Jolly-Seber and related models have recently been used to estimate survival rates of birds sampled with mist nets, we believe that the full potential for use of capture-recapture models has not been realized by many researchers involved in mist-net studies. We present a brief discussion of the overall framework for estimation using capture-recapture methods, and review several areas in which recent statistical methods can be, but generally have not yet been, applied to mist-net studies. These areas include estimation of (I) rates of movement among areas; (2) survival rates in the presence of transients: (3) population sizes or migrating birds: (4) proportion of birds alive but not present at a breeding site (one definition of proportion of nonbreeding birds in a population): (5) population change and recruitment: and (6) species richness. Using these models will avoid the possible bias associated with use of indices. and provide statistically valid variance estimates and inference.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Monitoring bird populations with mist nets","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","usgsCitation":"Kendall, W., Sauer, J., Nichols, J., Pradel, R., and Hines, J., 2004, On the use of capture-recapture models in mist-net studies, chap. of Monitoring bird populations with mist nets, p. 173-181.","productDescription":"211","startPage":"173","endPage":"181","numberOfPages":"211","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203113,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af3e4b07f02db691abf","contributors":{"editors":[{"text":"Ralph, C. John","contributorId":71284,"corporation":false,"usgs":true,"family":"Ralph","given":"C.","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":507892,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Dunn, Erica H.","contributorId":35841,"corporation":false,"usgs":false,"family":"Dunn","given":"Erica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":507891,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":330539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, J.R. 0000-0002-4557-3019","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":66197,"corporation":false,"usgs":true,"family":"Sauer","given":"J.R.","affiliations":[],"preferred":false,"id":330541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":330538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pradel, R.","contributorId":85692,"corporation":false,"usgs":true,"family":"Pradel","given":"R.","affiliations":[],"preferred":false,"id":330542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, J.E. 0000-0001-5478-7230","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":36885,"corporation":false,"usgs":true,"family":"Hines","given":"J.E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":330540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":5200284,"text":"5200284 - 2004 - Biodiversity of Fungi : Inventory and Monitoring Methods","interactions":[],"lastModifiedDate":"2017-08-29T09:09:26","indexId":"5200284","displayToPublicDate":"2009-06-08T16:49:39","publicationYear":"2004","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Biodiversity of Fungi : Inventory and Monitoring Methods","docAbstract":"Biodiversity of Fungi is essential for anyone collecting and/or monitoring any fungi. Fascinating and beautiful, fungi are vital components of nearly all ecosystems and impact human health and our economy in a myriad of ways. Standardized methods for documenting diversity and distribution have been lacking. An wealth of information, especially regrading sampling protocols, compiled by an international team of fungal biologists, make Biodiversity of Fungi an incredible and fundamental resource for the study of organismal biodiversity. Chapters cover everything from what is a fungus, to maintaining and organizing a permanent study collection with associated databases; from protocols for sampling slime molds to insect associated fungi; from fungi growing on and in animals and plants to mushrooms and truffles. The chapters are arranged both ecologically and by sampling method rather than by taxonomic group for ease of use. The information presented here is intended for everyone interested in fungi, anyone who needs tools to study them in nature including naturalists, land managers, ecologists, mycologists, and even citizen scientists and sophiscated amateurs. Fungi are among the most important organisms in the world; they play vital roles in ecosystem functions and have wide-ranging effects, both positive and negative, on humans and human-related activities. There are about 1.5 million species of fungi. The combination of fungal species and abundances in an ecosystem are often used as indicators of ecosystem health and as indicators of the effects of pollution and of different management and use plans. Because of their significance, it is important that these organisms be monitored. This book is the first comprehensive treatment of fungal inventory and monitoring, including standardized sampling protocols as well as information on study design, sample preservation, and data analysis.","language":"English","publisher":"Elsevier Academic Press","publisherLocation":"Boston,MA","usgsCitation":"2004, Biodiversity of Fungi : Inventory and Monitoring Methods, xviii, 777 p.","productDescription":"xviii, 777 p.","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201254,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4be4b07f02db625cfc","contributors":{"editors":[{"text":"Mueller, G.M.","contributorId":113869,"corporation":false,"usgs":true,"family":"Mueller","given":"G.M.","email":"","affiliations":[],"preferred":false,"id":505866,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Bills, G.F.","contributorId":103392,"corporation":false,"usgs":true,"family":"Bills","given":"G.F.","email":"","affiliations":[],"preferred":false,"id":505865,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Foster, M.S. 0000-0001-8272-4608","orcid":"https://orcid.org/0000-0001-8272-4608","contributorId":10116,"corporation":false,"usgs":true,"family":"Foster","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":505864,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}} ,{"id":5200285,"text":"5200285 - 2004 - Species Conservation and Management: Case Studies","interactions":[],"lastModifiedDate":"2012-02-02T00:15:18","indexId":"5200285","displayToPublicDate":"2009-06-08T16:49:39","publicationYear":"2004","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Species Conservation and Management: Case Studies","docAbstract":"This edited volume is a collection of population and metapopulation models for a wide variety of species, including plants, invertebrates, fishes, amphibians, reptiles, birds, and mammals. Each chapter of the book describes the application of RAMAS GIS 4.0 to one species, with the aim of demonstrating how various life history characteristics of the species are incorporated into the model, and how the results of the model has been or can be used in conservation and management of the species. The book comes with a CD that includes a demo version of the program, and the data files for each species.","language":"English","publisher":"Oxford University Press","publisherLocation":"New York","collaboration":"Visit URL for table of contents. OCLC: 52547617 ","usgsCitation":"Akcakaya, H., Burgman, M., Kindvall, O., Wood, C., Sjogren-Gulve, P., Hatfield, J., and McCarthy, M., 2004, Species Conservation and Management: Case Studies, xv, 533.","productDescription":"xv, 533","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201315,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e4e4b07f02db5e60a7","contributors":{"authors":[{"text":"Akcakaya, H.R.","contributorId":78442,"corporation":false,"usgs":true,"family":"Akcakaya","given":"H.R.","email":"","affiliations":[],"preferred":false,"id":327420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgman, M.A.","contributorId":88851,"corporation":false,"usgs":true,"family":"Burgman","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":327421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kindvall, O.","contributorId":18877,"corporation":false,"usgs":true,"family":"Kindvall","given":"O.","email":"","affiliations":[],"preferred":false,"id":327417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, C.C.","contributorId":17738,"corporation":false,"usgs":true,"family":"Wood","given":"C.C.","email":"","affiliations":[],"preferred":false,"id":327416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sjogren-Gulve, P.","contributorId":76044,"corporation":false,"usgs":true,"family":"Sjogren-Gulve","given":"P.","affiliations":[],"preferred":false,"id":327419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hatfield, Jeff S.","contributorId":41372,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeff S.","affiliations":[],"preferred":false,"id":327418,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCarthy, M.A.","contributorId":104595,"corporation":false,"usgs":true,"family":"McCarthy","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":327422,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":97161,"text":"ofr20041231 - 2004 - Rhode Island Water Supply System Management Plan Database (WSSMP-Version 1.0)","interactions":[],"lastModifiedDate":"2012-03-08T17:16:25","indexId":"ofr20041231","displayToPublicDate":"2008-12-23T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1231","title":"Rhode Island Water Supply System Management Plan Database (WSSMP-Version 1.0)","docAbstract":"In Rhode Island, the availability of water of sufficient quality and quantity to meet current and future environmental and economic needs is vital to life and the State's economy. Water suppliers, the Rhode Island Water Resources Board (RIWRB), and other State agencies responsible for water resources in Rhode Island need information about available resources, the water-supply infrastructure, and water use patterns. These decision makers need historical, current, and future water-resource information. In 1997, the State of Rhode Island formalized a system of Water Supply System Management Plans (WSSMPs) to characterize and document relevant water-supply information. All major water suppliers (those that obtain, transport, purchase, or sell more than 50 million gallons of water per year) are required to prepare, maintain, and carry out WSSMPs. An electronic database for this WSSMP information has been deemed necessary by the RIWRB for water suppliers and State agencies to consistently document, maintain, and interpret the information in these plans. Availability of WSSMP data in standard formats will allow water suppliers and State agencies to improve the understanding of water-supply systems and to plan for future needs or water-supply emergencies. In 2002, however, the Rhode Island General Assembly passed a law that classifies some of the WSSMP information as confidential to protect the water-supply infrastructure from potential terrorist threats. Therefore the WSSMP database was designed for an implementation method that will balance security concerns with the information needs of the RIWRB, suppliers, other State agencies, and the public.\r\n\r\nA WSSMP database was developed by the U.S. Geological Survey in cooperation with the RIWRB. The database was designed to catalog WSSMP information in a format that would accommodate synthesis of current and future information about Rhode Island's water-supply infrastructure. This report documents the design and implementation of the WSSMP database. All WSSMP information in the database is, ultimately, linked to the individual water suppliers and to a WSSMP 'cycle' (which is currently a 5-year planning cycle for compiling WSSMP information). The database file contains 172 tables - 47 data tables, 61 association tables, 61 domain tables, and 3 example import-link tables. This database is currently implemented in the Microsoft Access database software because it is widely used within and outside of government and is familiar to many existing and potential customers.\r\n\r\nDesign documentation facilitates current use and potential modification for future use of the database. Information within the structure of the WSSMP database file (WSSMPv01.mdb), a data dictionary file (WSSMPDD1.pdf), a detailed database-design diagram (WSSMPPL1.pdf), and this database-design report (OFR2004-1231.pdf) documents the design of the database. This report includes a discussion of each WSSMP data structure with an accompanying database-design diagram. Appendix 1 of this report is an index of the diagrams in the report and on the plate; this index is organized by table name in alphabetical order. Each of these products is included in digital format on the enclosed CD-ROM to facilitate use or modification of the database.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20041231","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board; A contribution to the Rhode Island Water Use Compilation","usgsCitation":"Granato, G., 2004, Rhode Island Water Supply System Management Plan Database (WSSMP-Version 1.0) (Version 1.0): U.S. Geological Survey Open-File Report 2004-1231, Report: viii, 77 p.; Plate: 36 x 48 inches; Zip File (contains data dictionary and RIWSSMP database), https://doi.org/10.3133/ofr20041231.","productDescription":"Report: viii, 77 p.; Plate: 36 x 48 inches; Zip File (contains data dictionary and RIWSSMP database)","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"links":[{"id":195729,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12146,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1231/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ae4b07f02db5fb3e0","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":301223,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97052,"text":"ofr20041456 - 2004 - Report of the U.S. Geological Survey Lidar Workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002","interactions":[],"lastModifiedDate":"2018-03-08T10:20:23","indexId":"ofr20041456","displayToPublicDate":"2008-10-25T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1456","title":"Report of the U.S. Geological Survey Lidar Workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002","docAbstract":"The first United States Geological Survey (USGS) Light Detection And Ranging (lidar) Workshop was held November 20-22, 2002 in St. Petersburg, Florida to bring together scientists and managers from across the agency. The workshop agenda focused on six themes: 1) current and future lidar technologies, 2) lidar applications within USGS science and disciplines, 3) calibration and accuracy assessment, 4) tools for processing and evaluating lidar data sets, 5) lidar data management, and 6) commercial and contracting issues. These six themes served as the topics for workshop plenary sessions as well as the general focus for associated breakout sessions. A number of recommendations are presented regarding the role the USGS should play in the future application and development of lidar technology.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041456","usgsCitation":"Crane, M., Clayton, T., Raabe, E., Stoker, J.M., Handley, L., Bawden, G.W., Morgan, K., and Queija, V., 2004, Report of the U.S. Geological Survey Lidar Workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p., https://doi.org/10.3133/ofr20041456.","productDescription":"72 p.","temporalStart":"2002-11-20","temporalEnd":"2002-11-22","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":196250,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12023,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1456/","linkFileType":{"id":5,"text":"html"}},{"id":338457,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2004/1456/pdf/ofr2004-1456.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a2ae4b07f02db61248a","contributors":{"authors":[{"text":"Crane, Michael","contributorId":92307,"corporation":false,"usgs":true,"family":"Crane","given":"Michael","email":"","affiliations":[],"preferred":false,"id":300903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clayton, Tonya","contributorId":6963,"corporation":false,"usgs":true,"family":"Clayton","given":"Tonya","affiliations":[],"preferred":false,"id":300899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raabe, Ellen","contributorId":98402,"corporation":false,"usgs":true,"family":"Raabe","given":"Ellen","affiliations":[],"preferred":false,"id":300904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":300897,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Handley, Larry","contributorId":66803,"corporation":false,"usgs":true,"family":"Handley","given":"Larry","email":"","affiliations":[],"preferred":false,"id":300901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bawden, Gerald W. gbawden@usgs.gov","contributorId":1071,"corporation":false,"usgs":true,"family":"Bawden","given":"Gerald","email":"gbawden@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":300900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morgan, Karen 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":88050,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen","affiliations":[],"preferred":false,"id":300902,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Queija, Vivian R. vqueija@usgs.gov","contributorId":4266,"corporation":false,"usgs":true,"family":"Queija","given":"Vivian R.","email":"vqueija@usgs.gov","affiliations":[],"preferred":false,"id":300898,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":80041,"text":"twri09A5.6.4.B - 2004 - Chapter A5. Section 6.4.B. Low-Level Mercury","interactions":[],"lastModifiedDate":"2012-02-02T00:14:06","indexId":"twri09A5.6.4.B","displayToPublicDate":"2007-06-20T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":336,"text":"Techniques of Water-Resources Investigations","code":"TWRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"09-A5.6.4.B","title":"Chapter A5. Section 6.4.B. Low-Level Mercury","docAbstract":"Collecting and processing water samples for analysis of mercury at a low (subnanogram per liter) level requires use of ultratrace-level techniques for equipment cleaning, sample collection, and sample processing. Established techniques and associated quality-assurance (QA) procedures for the collection and processing of water samples for trace-element analysis at the part-per-billion level (NFM 3-5) are not adequate for low-level mercury samples. Modifications to the part-per-billion procedures are necessary to minimize contamination of samples at a typical ambient mercury concentration, which commonly is at the subnanogram-per-liter level.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"National Field Manual for the Collection of Water-Quality Data. U.S. Geological Survey Techniques of Water-Resources Investigations, Book 9","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/twri09A5.6.4.B","usgsCitation":"Lewis, M.E., and Brigham, M.E., 2004, Chapter A5. Section 6.4.B. Low-Level Mercury (Version 1.0): U.S. Geological Survey Techniques of Water-Resources Investigations 09-A5.6.4.B, 26 p., https://doi.org/10.3133/twri09A5.6.4.B.","productDescription":"26 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":193077,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9800,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://water.usgs.gov/owq/FieldManual/chapter5/pdf/5.6.4.B_v1.0.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":9799,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://water.usgs.gov/owq/FieldManual/chapter5/html/Ch5_contents.html","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e3e4b07f02db5e59e8","contributors":{"authors":[{"text":"Lewis, Michael Edward","contributorId":60726,"corporation":false,"usgs":true,"family":"Lewis","given":"Michael","email":"","middleInitial":"Edward","affiliations":[],"preferred":false,"id":291547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":291546,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":78977,"text":"ofr20041070 - 2004 - Converting analog interpretive data to digital formats for use in database and GIS applications","interactions":[],"lastModifiedDate":"2014-08-20T09:25:01","indexId":"ofr20041070","displayToPublicDate":"2006-08-28T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1070","title":"Converting analog interpretive data to digital formats for use in database and GIS applications","docAbstract":"There is a growing need by researchers and managers for comprehensive and unified nationwide datasets of scientific data. These datasets must be in a digital format that is easily accessible using database and GIS applications, providing the user with access to a wide variety of current and historical information. Although most data currently being collected by scientists are already in a digital format, there is still a large repository of information in the literature and paper archive. Converting this information into a format accessible by computer applications is typically very difficult and can result in loss of data. However, since scientific data are commonly collected in a repetitious, concise matter (i.e., forms, tables, graphs, etc.), these data can be recovered digitally by using a conversion process that relates the position of an attribute in two-dimensional space to the information that the attribute signifies. For example, if a table contains a certain piece of information in a specific row and column, then the space that the row and column occupies becomes an index of that information. An index key is used to identify the relation between the physical location of the attribute and the information the attribute contains. The conversion process can be achieved rapidly, easily and inexpensively using widely available digitizing and spreadsheet software, and simple programming code. \n\nIn the geological sciences, sedimentary character is commonly interpreted from geophysical profiles and descriptions of sediment cores. In the field and laboratory, these interpretations were typically transcribed to paper. The information from these paper archives is still relevant and increasingly important to scientists, engineers and managers to understand geologic processes affecting our environment. Direct scanning of this information produces a raster facsimile of the data, which allows it to be linked to the electronic world. But true integration of the content with database and GIS software as point, vector or text information is commonly lost. Sediment core descriptions and interpretation of geophysical profiles are usually portrayed as lines, curves, symbols and text information. They have vertical and horizontal dimensions associated with depth, category, time, or geographic position. These dimensions are displayed in consistent positions, which can be digitized and converted to a digital format, such as a spreadsheet. Once this data is in a digital, tabulated form it can easily be made available to a wide variety of imaging and data manipulation software for compilation and world-wide dissemination.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20041070","usgsCitation":"Flocks, J.G., 2004, Converting analog interpretive data to digital formats for use in database and GIS applications: U.S. Geological Survey Open-File Report 2004-1070, xiii, 26 p., https://doi.org/10.3133/ofr20041070.","productDescription":"xiii, 26 p.","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":126382,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2004_1070.jpg"},{"id":14139,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1070/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4781e4b07f02db482945","contributors":{"authors":[{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":289019,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":78975,"text":"ofr20041065 - 2004 - Herpetofaunal inventories of the National Parks of South Florida and the Caribbean: Volume I. Everglades National Park","interactions":[],"lastModifiedDate":"2017-03-08T11:25:20","indexId":"ofr20041065","displayToPublicDate":"2006-08-28T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1065","title":"Herpetofaunal inventories of the National Parks of South Florida and the Caribbean: Volume I. Everglades National Park","docAbstract":"Amphibian declines and extinctions have been documented around the world, often in protected natural areas. Concern for this alarming trend has prompted the U.S. Geological Survey and the National Park Service to document all species of amphibians that occur within U.S. National Parks and to search for any signs that amphibians may be declining. This study, an inventory of amphibian species in Everglades National Park, was conducted during 2000 to 2003. The goals of the project were to create a georeferenced inventory of amphibian species, use new analytical techniques to estimate proportion of sites occupied by each species, look for any signs of amphibian decline (missing species, disease, die-offs, etc.), and to establish a protocol that could be used for future monitoring efforts.\r\n\r\nSeveral sampling methods were used to accomplish all of these goals. Visual encounter surveys and anuran vocalization surveys were conducted in all habitats throughout the park to estimate the proportion of sites or proportion of area occupied (PAO) by each amphibian species in each habitat. Opportunistic collections, as well as some drift fence and aquatic funnel trap data were used to augment the visual encounter methods for highly aquatic or cryptic species. A total of 562 visits to 118 sites were conducted for standard sampling alone, and 1788 individual amphibians and 413 reptiles were encountered. Data analysis was done in program PRESENCE to provide PAO estimates for each of the anuran species.\r\n\r\nAll but one of the amphibian species thought to occur in Everglades National Park was detected during this project. That species, the Everglades dwarf siren (Pseudobranchus axanthus belli), is especially cryptic and probably geographically limited in its range in Everglades National Park. The other three species of salamanders and all of the anurans in the park were sampled adequately using standard herpetological sampling methods. PAO estimates were produced for each species of anuran by habitat. This information is valuable now as an indicator of habitat associations of the species and relative abundance of sites occupied, but it will also be useful as a comparative baseline for future monitoring efforts.\r\n\r\nIn addition to sampling for amphibians, all encounters with reptiles were documented. The sampling methods used for detecting amphibians are also appropriate for many reptile species. These reptile locations are included in this report, but there were not enough locations for most reptile species to analyze the PAO of individual species. 37 of the 57 species of reptiles thought to occur in Everglades National Park were detected during this study.\r\n\r\nThis study found no evidence of amphibian decline in Everglades National Park. There was one species not detected, but there is no evidence to indicate it has been extirpated from the park. Although no declines were observed, several threats to amphibians were identified. Introduced species, especially the Cuban treefrog (Osteopilus septentrionalis), are predators and competitors with several native frog species. Also, interference by humans with the natural hydrological cycle of the Everglades has the potential to alter the amphibian community. Finally, habitat loss outside the park has the potential to leave the amphibians in Everglades National Park isolated from other populations.\r\n\r\nContinued monitoring of the amphibian species in Everglades National Park is recommended. The methods used in this study are adequate to produce reliable estimates of the proportion of sites occupied by most anuran species. Continuing this protocol is a cost-effective way of determining whether species are decreasing or increasing in abundance of sites occupied.\r\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041065","usgsCitation":"Rice, K.G., Waddle, J., Crockett, M.E., Jeffery, B.M., and Percival, H., 2004, Herpetofaunal inventories of the National Parks of South Florida and the Caribbean: Volume I. Everglades National Park: U.S. Geological Survey Open-File Report 2004-1065, 144 p., https://doi.org/10.3133/ofr20041065.","productDescription":"144 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":275,"text":"Florida Integrated Science Center","active":false,"usgs":true}],"links":[{"id":124583,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2004_1065.jpg"},{"id":337047,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7MJ9","text":"Data for herpetofaunal inventories of the national parks of South Florida and the Caribbean: Volume I, Everglades National Park"},{"id":337046,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2004/1065/pdf/of04-1065.pdf"},{"id":13882,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1065/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db635bb5","contributors":{"authors":[{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":289014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":289018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crockett, Marquette E.","contributorId":70067,"corporation":false,"usgs":true,"family":"Crockett","given":"Marquette","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":289017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jeffery, Brian M.","contributorId":16511,"corporation":false,"usgs":false,"family":"Jeffery","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":289015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Percival, H. Frankin","contributorId":40286,"corporation":false,"usgs":true,"family":"Percival","given":"H. Frankin","affiliations":[],"preferred":false,"id":289016,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":77382,"text":"i2600 - 2004 - Coastal-change and glaciological maps of Antarctica","interactions":[],"lastModifiedDate":"2013-05-08T15:18:46","indexId":"i2600","displayToPublicDate":"2006-07-27T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2600","title":"Coastal-change and glaciological maps of Antarctica","docAbstract":"Changes in the area and volume of polar ice sheets are intricately linked to changes in global climate, and the resulting changes in sea level may severely impact the densely populated coastal regions on Earth. Melting of the West Antarctic part alone of the Antarctic ice sheet could cause a sea-level rise of approximately 6 meters (m). The potential sea-level rise after melting of the entire Antarctic ice sheet is estimated to be 65 m (Lythe and others, 2001) to 73 m (Williams and Hall, 1993). In spite of its importance, the mass balance (the net volumetric gain or loss) of the Antarctic ice sheet is poorly known; it is not known for certain whether the ice sheet is growing or shrinking. In a review paper, Rignot and Thomas (2002) concluded that the West Antarctic part of the Antarctic ice sheet is probably becoming thinner overall; although the western part is thickening, the northern part is thinning. Joughin and Tulaczyk (2002), based on analysis of ice-flow velocities derived from synthetic aperture radar, concluded that most of the Ross ice streams (ice streams on the east side of the Ross Ice Shelf) have a positive mass balance. The mass balance of the East Antarctic is unknown, but thought to be in near equilibrium.\n\nMeasurement of changes in area and mass balance of the Antarctic ice sheet was given a very high priority in recommendations by the Polar Research Board of the National Research Council (1986), in subsequent recommendations by the Scientific Committee on Antarctic Research (SCAR) (1989, 1993), and by the National Science Foundation's (1990) Division of Polar Programs. On the basis of these recommendations, the U.S. Geological Survey (USGS) decided that the archive of early 1970s Landsat 1, 2, and 3 Multispectral Scanner (MSS) images of Antarctica and the subsequent repeat coverage made possible with Landsat and other satellite images provided an excellent means of documenting changes in the coastline of Antarctica (Ferrigno and Gould, 1987). The availability of this information provided the impetus for carrying out a comprehensive analysis of the glaciological features of the coastal regions and changes in ice fronts of Antarctica (Swithinbank, 1988; Williams and Ferrigno, 1988). The project was later modified to include Landsat 4 and 5 MSS and Thematic Mapper (TM) (and in some areas Landsat 7 Enhanced Thematic Mapper Plus (ETM+)), RADARSAT images, and other data where available, to compare changes over a 20- to 25- or 30-year time interval (or longer where data were available, as in the Antarctic Peninsula). The results of the analysis are being used to produce a digital database and a series of USGS Geologic Investigations Series Maps consisting of 24 maps at 1:1,000,000 scale and 1 map at 1:5,000,000 scale, in both paper and digital format (Williams and others, 1995; Williams and Ferrigno, 1998; and Ferrigno and others, 2002).","language":"ENGLISH","doi":"10.3133/i2600","usgsCitation":"Williams, R.S., 2004, Coastal-change and glaciological maps of Antarctica: U.S. Geological Survey IMAP 2600, Variously paginated, https://doi.org/10.3133/i2600.","productDescription":"Variously paginated","costCenters":[],"links":[{"id":192406,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/i2600.png"},{"id":8351,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2600/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4779e4b07f02db47f0af","contributors":{"authors":[{"text":"Williams, Richard S. Jr.,(compiler)","contributorId":96364,"corporation":false,"usgs":true,"family":"Williams","given":"Richard","suffix":"Jr.,(compiler)","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":288506,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":76996,"text":"ofr2003496 - 2004 - Water quality and quantity of selected springs and seeps along the Colorado River corridor, Utah and Arizona: Arches National Park, Canyonlands National Park, Glen Canyon National Recreation Area, and Grand Canyon National Park, 1997-98","interactions":[],"lastModifiedDate":"2012-02-02T00:14:18","indexId":"ofr2003496","displayToPublicDate":"2006-07-06T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2003-496","title":"Water quality and quantity of selected springs and seeps along the Colorado River corridor, Utah and Arizona: Arches National Park, Canyonlands National Park, Glen Canyon National Recreation Area, and Grand Canyon National Park, 1997-98","docAbstract":"The U.S. Geological Survey, in cooperation with the National Park Service conducted an intensive assessment of selected springs along the Colorado River Corridor in Arches National Park, Canyonlands National Park, Glen Canyon National Recreation Area, and Grand Canyon National Park in 1997 and 1998, for the purpose of measuring and evaluating the water quality and quantity of the resource. This study was conducted to establish baseline data for the future evaluation of possible effects from recreational use and climate change. Selected springs and seeps were visited over a study period from 1997 to 1998, during which, discharge and on-site chemical measurements were made at selected springs and seeps, and samples were collected for subsequent chemical laboratory analysis. This interdisciplinary study also includes simultaneous studies of flora and fauna, measured and sampled coincidently at the same sites. Samples collected during this study were transported to U.S. Geological Survey laboratories in Boulder, Colorado, where analyses were performed using state-of-the-art laboratory technology. The location of the selected springs and seeps, elevation, geology, aspect, and onsite measurements including temperature, discharge, dissolved oxygen, pH, and specific conductance, were recorded. Laboratory analyses include determinations for alkalinity, aluminum, ammonium (nitrogen), antimony, arsenic, barium, beryllium, bismuth, boron, bromide, cadmium, calcium, cerium, cesium, chloride, chromium, cobalt, copper, dissolved inorganic carbon, dissolved organic carbon, dysprosium, erbium, europium, fluoride, gadolinium, holmium, iodine, iron, lanthanum, lead, lithium, lutetium, magnesium, manganese, mercury, molybdenum, neodymium, nickel, nitrate (nitrogen), nitrite (nitrogen), phosphate, phosphorus, potassium, praseodymium, rhenium, rubidium, samarium, selenium, silica, silver, sodium, strontium, sulfate, tellurium, terbium, thallium, thorium, thulium, tin, titanium, tungsten, uranium, vanadium, yttrium, ytterbium, zinc, and zirconium in these springs and seeps. Biological observations include physical setting, vegetation, invertebrate habitats, and invertebrate microhabitats.","language":"ENGLISH","doi":"10.3133/ofr2003496","usgsCitation":"Taylor, H.E., Spence, J.R., Antweiler, R.C., Berghoff, K., Plowman, T.I., Peart, D.B., and Roth, D.A., 2004, Water quality and quantity of selected springs and seeps along the Colorado River corridor, Utah and Arizona: Arches National Park, Canyonlands National Park, Glen Canyon National Recreation Area, and Grand Canyon National Park, 1997-98: U.S. Geological Survey Open-File Report 2003-496, viii, 24 p., https://doi.org/10.3133/ofr2003496.","productDescription":"viii, 24 p.","numberOfPages":"32","additionalOnlineFiles":"Y","temporalStart":"1997-01-01","temporalEnd":"1998-12-31","costCenters":[],"links":[{"id":194546,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8222,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://wwwbrr.cr.usgs.gov/projects/SW_inorganic/download/","linkFileType":{"id":5,"text":"html"}},{"id":8221,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://wwwbrr.cr.usgs.gov/projects/SW_inorganic/download/CO%20Rv%20Springs.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":8223,"rank":9999,"type":{"id":18,"text":"Project Site"},"url":"https://wwwbrr.cr.usgs.gov/projects/SW_inorganic/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a08e4b07f02db5f9be8","contributors":{"authors":[{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":288256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spence, John R.","contributorId":27963,"corporation":false,"usgs":true,"family":"Spence","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":288259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Antweiler, Ronald C. 0000-0001-5652-6034 antweil@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-6034","contributorId":1481,"corporation":false,"usgs":true,"family":"Antweiler","given":"Ronald","email":"antweil@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":288255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berghoff, Kevin","contributorId":107805,"corporation":false,"usgs":true,"family":"Berghoff","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":288261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plowman, Terry I. tplowman@usgs.gov","contributorId":3727,"corporation":false,"usgs":true,"family":"Plowman","given":"Terry","email":"tplowman@usgs.gov","middleInitial":"I.","affiliations":[],"preferred":true,"id":288258,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peart, Dale B.","contributorId":86384,"corporation":false,"usgs":true,"family":"Peart","given":"Dale","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":288260,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roth, David A. 0000-0002-7515-3533 daroth@usgs.gov","orcid":"https://orcid.org/0000-0002-7515-3533","contributorId":2340,"corporation":false,"usgs":true,"family":"Roth","given":"David","email":"daroth@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":288257,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":77004,"text":"ofr20041325 - 2004 - A new method of edge detection for object recognition","interactions":[],"lastModifiedDate":"2012-04-15T17:28:14","indexId":"ofr20041325","displayToPublicDate":"2006-07-06T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1325","title":"A new method of edge detection for object recognition","docAbstract":"Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.","language":"ENGLISH","doi":"10.3133/ofr20041325","usgsCitation":"Maddox, B.G., and Rhew, B., 2004, A new method of edge detection for object recognition: U.S. Geological Survey Open-File Report 2004-1325, 17 p., https://doi.org/10.3133/ofr20041325.","productDescription":"17 p.","numberOfPages":"17","costCenters":[],"links":[{"id":193090,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8214,"rank":300,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1325/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b20e4b07f02db6abbe2","contributors":{"authors":[{"text":"Maddox, Brian G.","contributorId":57140,"corporation":false,"usgs":true,"family":"Maddox","given":"Brian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":288274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhew, Benjamin","contributorId":63490,"corporation":false,"usgs":true,"family":"Rhew","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":288275,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":77003,"text":"ofr20041324 - 2004 - Metadata for ReVA logistic regression dataset","interactions":[],"lastModifiedDate":"2023-03-10T13:12:31.493763","indexId":"ofr20041324","displayToPublicDate":"2006-07-06T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1324","title":"Metadata for ReVA logistic regression dataset","docAbstract":"The U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency's Regional Vulnerability Assessment Program, has developed a set of statistical tools to support regional-scale, ground-water quality and vulnerability assessments. The Regional Vulnerability Assessment Program goals are to develop and demonstrate approaches to comprehensive, regional-scale assessments that effectively inform water-resources managers and decision-makers as to the magnitude, extent, distribution, and uncertainty of current and anticipated environmental risks. The U.S. Geological Survey is developing and exploring the use of statistical probability models to characterize the relation between ground-water quality and geographic factors in the Mid-Atlantic Region. Available water-quality data obtained from U.S. Geological Survey National Water-Quality Assessment Program studies conducted in the Mid-Atlantic Region were used in association with geographic data (land cover, geology, soils, and others) to develop logistic-regression equations that use explanatory variables to predict the presence of a selected water-quality parameter exceeding specified management concentration thresholds. The resulting logistic-regression equations were transformed to determine the probability, P(X), of a water-quality parameter exceeding a specified management threshold. Additional statistical procedures modified by the U.S. Geological Survey were used to compare the observed values to model-predicted values at each sample point. In addition, procedures to evaluate the confidence of the model predictions and estimate the uncertainty of the probability value were developed and applied. The resulting logistic-regression models were applied to the Mid-Atlantic Region to predict the spatial probability of nitrate concentrations exceeding specified management thresholds. These thresholds are usually set or established by regulators or managers at national or local levels. At management thresholds of 1 milligram per liter, and 3 milligrams per liter, the probability of nitrate concentrations exceeding these levels is greater than 50 percent (.50) throughout much of the Mid-Atlantic Region. This includes extensive areas throughout central Maryland, southeastern Pennsylvania, northwestern Pennsylvania and the Delmarva Peninsula. In addition, extensive areas in North Carolina and Virginia also have high probabilities of nitrate concentrations in ground water exceeding management thresholds of 1 milligram per liter and 3 milligrams per liter. The mapped areas showing a high predicted probability of nitrate concentrations in ground water exceeding 1 milligram per liter and 3 milligrams per liter correspond to areas that are mapped as cultivated land cover overlying carbonate rocks. At a management threshold of 10 milligrams per liter (corresponding to the U.S. Environmental Protection Agency standard for nitrate in drinking water of 10 milligrams per liter), the predicted probability of nitrate concentrations in ground water exceeding this level are low for most of the Mid-Atlantic Region except for the Delmarva Peninsula, southeastern Pennsylvania, and areas mapped as carbonate rocks in Virginia, Maryland, and Pennsylvania.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20041324","usgsCitation":"LaMotte, A.E., 2004, Metadata for ReVA logistic regression dataset: U.S. Geological Survey Open-File Report 2004-1324, 9 p., https://doi.org/10.3133/ofr20041324.","productDescription":"9 p.","numberOfPages":"9","onlineOnly":"Y","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":8153,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://md.water.usgs.gov/publications/ofr-2004-1324/","linkFileType":{"id":5,"text":"html"}},{"id":194483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4be4b07f02db6255e6","contributors":{"authors":[{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":288273,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":76816,"text":"ofr2003117 - 2004 - Distributed Processing of Projections of Large Datasets: A Preliminary Study","interactions":[],"lastModifiedDate":"2012-04-15T17:28:15","indexId":"ofr2003117","displayToPublicDate":"2006-06-13T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2003-117","title":"Distributed Processing of Projections of Large Datasets: A Preliminary Study","docAbstract":"Modern information needs have resulted in very large amounts of data being used in geographic information systems. Problems arise when trying to project these data in a reasonable amount of time and accuracy, however. Current single-threaded methods can suffer from two problems: fast projection with poor accuracy, or accurate projection with long processing time. A possible solution may be to combine accurate interpolation methods and distributed processing algorithms to quickly and accurately convert digital geospatial data between coordinate systems. Modern technology has made it possible to construct systems, such as Beowulf clusters, for a low cost and provide access to supercomputer-class technology. Combining these techniques may result in the ability to use large amounts of geographic data in time-critical situations.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr2003117","usgsCitation":"Maddox, B.G., 2004, Distributed Processing of Projections of Large Datasets: A Preliminary Study: U.S. Geological Survey Open-File Report 2003-117, 19 p., https://doi.org/10.3133/ofr2003117.","productDescription":"19 p.","numberOfPages":"19","onlineOnly":"Y","costCenters":[{"id":384,"text":"Mid-Continent Mapping Center","active":false,"usgs":true}],"links":[{"id":192440,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":13239,"rank":300,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2003/0117/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a1dc","contributors":{"authors":[{"text":"Maddox, Brian G.","contributorId":57140,"corporation":false,"usgs":true,"family":"Maddox","given":"Brian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":287951,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":76672,"text":"wdrOH-31 - 2004 - Water resources data, Ohio, water year 2003 : Volume 1. Ohio River basin excluding project data","interactions":[],"lastModifiedDate":"2012-03-08T17:16:23","indexId":"wdrOH-31","displayToPublicDate":"2006-04-30T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":340,"text":"Water Data Report","code":"WDR","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"OH-03-1","title":"Water resources data, Ohio, water year 2003 : Volume 1. Ohio River basin excluding project data","docAbstract":"Water-resources data for the 2003 water year for Ohio consist of records of stage, discharge, and water quality of streams; stage and contents of lakes and reservoirs; and water levels and water quality of ground-water wells. This report, in two volumes, contains records for water discharge at 138 gaging stations and various partial-record sites; water levels at 217 observation wells and 35 crest-stage gages; and water quality at 30 gaging stations, 34 observation wells, and no partial-record sites. Also included are data from miscellaneous and synoptic sites. Additional water data were collected at various sites not involved in the systematic data-collection program and are published as miscellaneous measurements and analyses. These data represent that part of the National Water Information System collected by the U.S. Geological Survey and cooperating Federal, State, and local agencies in Ohio.","language":"ENGLISH","doi":"10.3133/wdrOH-31","usgsCitation":"Shindel, H., Mangus, J., and Frum, S., 2004, Water resources data, Ohio, water year 2003 : Volume 1. 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Volume 1. Hawaii","interactions":[],"lastModifiedDate":"2012-03-08T17:16:20","indexId":"wdrHI031","displayToPublicDate":"2006-04-19T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":340,"text":"Water Data Report","code":"WDR","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"HI-03-1","title":"Water Resources Data: Hawaii and Other Pacific Areas, Water Year 2003. Volume 1. 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