Variation in food resource availability can have profound effects on habitat selection and dynamics of populations. Previous studies reported higher food resource availability and fruit removal in treefall gaps than in the understorey. Therefore, gaps have been considered 'keystone habitat' for Neotropical frugivore birds. Here we test if this prediction would also hold for terrestrial small mammals. In the Amazon, we quantified food resource availability in eleven treefall gaps and paired understorey habitats and used feeding experiments to test if two common terrestrial rodents (Oryzomys megacephalus and Proechimys spp.) would perceive differences between habitats. We live-trapped small mammals in eleven gaps and understorey sites for two years, and compared abundance, fitness components (survival and per capita recruitment) and dispersal of these two rodent species across gaps and understorey and seasons (rainy and dry). Our data indicated no differences in resource availability and consumption rate between habitats. Treefall gaps may represent a sink habitat for Oryzomys where individuals had lower fitness, apparently because of habitat-specific ant predation on early life stages, than in the understorey, the source habitat. Conversely, gaps may be source habitat for Proechimys where individuals had higher fitness, than in the understorey, the sink habitat. Our results suggest the presence of source-sink dynamics in a tropical gap-understorey landscape, where two rodent species perceive habitats differently. This may be a mechanism for their coexistence in a heterogeneous and species-diverse system.
","language":"English","publisher":"Wiley","doi":"10.1111/j.0030-1299.2004.12864.x","usgsCitation":"Beck, H., Gaines, M., Hines, J., and Nichols, J., 2004, Comparative dynamics of small mammal populations in treefall gaps and surrounding understorey within Amazonian rainforest: Oikos, v. 106, no. 1, p. 27-38, https://doi.org/10.1111/j.0030-1299.2004.12864.x.","productDescription":"12 p.","startPage":"27","endPage":"38","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":477993,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.0030-1299.2004.12864.x","text":"Publisher Index Page"},{"id":199516,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"World Biosphere Park Manu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.82617187499999,\n -4.653079918274076\n ],\n [\n -79.453125,\n -8.320212289522969\n ],\n [\n -77.255859375,\n -13.325484885597936\n ],\n [\n -74.267578125,\n -16.214674588248542\n ],\n [\n -69.87304687499997,\n -18.396230138028837\n ],\n [\n -68.90624999999997,\n -16.3833911236084\n ],\n [\n -68.99414062499999,\n -14.944784875088386\n ],\n [\n -68.81835937499999,\n -12.811801316582631\n ],\n [\n -69.52148437499999,\n -11.092165893502013\n ],\n [\n -70.400390625,\n -9.535748998133615\n ],\n [\n -71.455078125,\n -9.535748998133615\n ],\n [\n -72.77343749999997,\n -9.102096738726468\n ],\n [\n -73.47656249999999,\n -7.188100871179045\n ],\n [\n -72.42187499999999,\n -5.5285105256928135\n ],\n [\n -71.015625,\n -5.003394345022175\n ],\n [\n -70.04882812499997,\n -3.6888551431470478\n ],\n [\n -69.60937499999999,\n -2.2845506602369827\n ],\n [\n -73.12499999999999,\n -1.406108835435185\n ],\n [\n -75.32226562499999,\n -2.5444437451708134e-14\n ],\n [\n -75.93749999999999,\n -1.3182430568620263\n ],\n [\n -77.16796875,\n -2.3723687086440757\n ],\n [\n -79.01367187499997,\n -4.039617826768462\n ],\n [\n -80.59570312499999,\n -3.162455530237873\n ],\n [\n -81.82617187499999,\n -4.653079918274076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"1","noUsgsAuthors":false,"publicationDate":"2004-05-17","publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae56d","contributors":{"authors":[{"text":"Beck, H.","contributorId":27587,"corporation":false,"usgs":true,"family":"Beck","given":"H.","email":"","affiliations":[],"preferred":false,"id":341210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaines, M.S.","contributorId":70887,"corporation":false,"usgs":true,"family":"Gaines","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":341212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":341211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":341209,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":5224309,"text":"5224309 - 2004 - Passive tick surveillance, dog seropositivity, and incidence of human Lyme disease","interactions":[],"lastModifiedDate":"2016-12-07T14:42:58","indexId":"5224309","displayToPublicDate":"2010-06-16T12:18:50","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3675,"text":"Vector-Borne and Zoonotic Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Passive tick surveillance, dog seropositivity, and incidence of human Lyme disease","docAbstract":"Data on nymphal Ixodes scapularis ticks submitted by the public to the University of Rhode Island Tick Research Laboratory for testing from 1991 to 2000 were compared with human case data from the Rhode Island Department of Health to determine the efficacy of passive tick surveillance at assessing human risk of Lyme disease. Numbers of ticks submitted were highly correlated with human cases by county (r = 0.998, n = 5 counties) and by town (r = 0.916, n = 37 towns), as were the numbers of positive ticks submitted (r = 0.989 by county, r = 0.787 by town). Human cases were correlated with ticks submitted by town each year, and with positive ticks in all but 2 years. Thus, passive tick surveillance effectively assessed geographical risk of human Lyme disease. In contrast, tick submissions through time were not correlated with human cases from year to year. Dog seropositivity was significantly correlated with human cases by county in both years tested, but by town in only one of two years. Numbers of ticks submitted were correlated with dog seropositivity by county but not by town, apparently because of high variability among towns with small sample sizes. Our results suggest that passive tick surveillance, using ticks submitted by the public for Lyme spirochete testing, can be used to assess the geographical distribution of Lyme disease risk, but cannot reliably predict Lyme incidence from year to year.
","language":"English","publisher":"Mary Ann Liebert, Inc.","doi":"10.1089/1530366041210710","usgsCitation":"Johnson, J.L., Ginsberg, H.S., Zhioua, E., Whitworth, U.G., Markowski, D., Hyland, K.E., and Hu, R., 2004, Passive tick surveillance, dog seropositivity, and incidence of human Lyme disease: Vector-Borne and Zoonotic Diseases, v. 4, no. 2, p. 137-142, https://doi.org/10.1089/1530366041210710.","productDescription":"6 p.","startPage":"137","endPage":"142","numberOfPages":"6","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":487140,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/167","text":"External Repository"},{"id":201509,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4994e4b07f02db5b5f93","contributors":{"authors":[{"text":"Johnson, Jaree L.","contributorId":177249,"corporation":false,"usgs":false,"family":"Johnson","given":"Jaree","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":341231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. hginsberg@usgs.gov","contributorId":140901,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","email":"hginsberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":341226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhioua, Elyes","contributorId":177231,"corporation":false,"usgs":true,"family":"Zhioua","given":"Elyes","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":341225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitworth, Ulysses G.","contributorId":94415,"corporation":false,"usgs":true,"family":"Whitworth","given":"Ulysses","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":341230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Markowski, Daniel","contributorId":177250,"corporation":false,"usgs":false,"family":"Markowski","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":341229,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hyland, Kerwin E.","contributorId":177251,"corporation":false,"usgs":false,"family":"Hyland","given":"Kerwin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":341228,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hu, Renjie","contributorId":177252,"corporation":false,"usgs":false,"family":"Hu","given":"Renjie","email":"","affiliations":[],"preferred":false,"id":341227,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":5224310,"text":"5224310 - 2004 - Native bees and plant pollination","interactions":[],"lastModifiedDate":"2012-02-02T00:15:04","indexId":"5224310","displayToPublicDate":"2010-06-16T12:18:50","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3296,"text":"Rhode Island Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Native bees and plant pollination","docAbstract":"Bees are important pollinators, but evidence suggests that numbers of some species are declining. Decreases have been documented in the honey bee, Apis mellifera (which was introduced to North America), but there are no monitoring programs for the vast majority of native species, so we cannot be sure about the extent of this problem. Recent efforts to develop standardized protocols for bee sampling will help us collect the data needed to assess trends in bee populations. Unfortunately, diversity of bee life cycles and phenologies, and the large number of rare species, make it difficult to assess trends in bee faunas. Changes in bee populations can affect plant reproduction, which can influence plant population density and cover, thus potentially modifying horizontal and vertical structure of a community, microclimate near the ground, patterns of nitrogen deposition, etc. These potential effects of changes in pollination patterns have not been assessed in natural communities. Effects of management actions on bees and other pollinators should be considered in conservation planning. ","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rhode Island Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","collaboration":"6159_Ginsberg.pdf","usgsCitation":"Ginsberg, H., 2004, Native bees and plant pollination: Rhode Island Naturalist, v. 11, no. 1, p. 1-3.","productDescription":"1-3","startPage":"1","endPage":"3","numberOfPages":"3","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":198141,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b28e4b07f02db6b10dc","contributors":{"authors":[{"text":"Ginsberg, H. S. 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":27576,"corporation":false,"usgs":true,"family":"Ginsberg","given":"H. S.","affiliations":[],"preferred":false,"id":341232,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":5224301,"text":"5224301 - 2004 - Extinction rate estimates for plant populations in revisitation studies: Importance of detectability","interactions":[],"lastModifiedDate":"2021-08-06T16:31:21.678762","indexId":"5224301","displayToPublicDate":"2010-06-16T12:18:50","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Extinction rate estimates for plant populations in revisitation studies: Importance of detectability","docAbstract":"Many researchers have obtained extinction-rate estimates for plant populations by comparing historical and current records of occurrence. A population that is no longer found is assumed to have gone extinct. Extinction can then be related to characteristics of these populations, such as habitat type, size, or species, to test ideas about what factors may affect extinction. Such studies neglect the fact that a population may be overlooked, however, which may bias estimates of extinction rates upward. In addition, if populations are unequally detectable across groups to be compared, such as habitat type or population size, comparisons become distorted to an unknown degree. To illustrate the problem, I simulated two data sets, assuming a constant extinction rate, in which populations occurred in different habitats or habitats of different size and these factors affected their detectability The conventional analysis implicitly assumed that detectability equalled 1 and used logistic regression to estimate extinction rates. It wrongly identified habitat and population size as factors affecting extinction risk. In contrast, with capture-recapture methods, unbiased estimates of extinction rates were recovered. I argue that capture-recapture methods should be considered more often in estimations of demographic parameters in plant populations and communities.","language":"English","publisher":"Wiley Online Library","doi":"10.1111/j.1523-1739.2004.00105.x","usgsCitation":"Kery, M., 2004, Extinction rate estimates for plant populations in revisitation studies: Importance of detectability: Conservation Biology, v. 18, no. 2, p. 570-574, https://doi.org/10.1111/j.1523-1739.2004.00105.x.","productDescription":"5 p.","startPage":"570","endPage":"574","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":199447,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2004-03-19","publicationStatus":"PW","scienceBaseUri":"4f4e4a06e4b07f02db5f8a33","contributors":{"authors":[{"text":"Kery, M.","contributorId":46637,"corporation":false,"usgs":true,"family":"Kery","given":"M.","affiliations":[],"preferred":false,"id":341195,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":5224290,"text":"5224290 - 2004 - Monitoring programs need to take into account imperfect species detectability","interactions":[],"lastModifiedDate":"2012-02-02T00:15:37","indexId":"5224290","displayToPublicDate":"2010-06-16T12:18:50","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":970,"text":"Basic and Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring programs need to take into account imperfect species detectability","docAbstract":"Biodiversiry monitoring is important to identify biological units in need of conservation and to check the effectiveness of conservation actions. Programs generally monitor species richness and its changes (trend). Usually, no correction is made for imperfect species detectability. Instead, it is assumed that each species present has the same probability of being recorded and that there is no difference in this detectability across space and time, e.g. among observers and habitats. Consequently, species richness is determined by enumeration as the sum of species recorded. In Switzerland, the federal government has recently launched a comprehensive program that aims at detecting changes in biodiversity at all levels of biological integration. Birds are an important part of that program. Since 1999, 23 visits per breeding season are made to each of >250 1 km2 squares to map the territories of all detected breeding bird species. Here, we analyse data from three squares to illustrate the use of capture-recapture models in monitoring to obtain detectability-corrected estimates of species richness and trend. Species detectability averaged only 85%. Hence an estimated 15% of species present remained overlooked even after three visits. Within a square, changes in detectability for different years were of the same magnitude when surveys were conducted by the same observer as when they were by different observers. Estimates of trend were usually biased and community turnover was overestimated when based on enumeration. Here we use bird data as an illustration of methods. However, species detectability for any taxon is unlikely ever to be perfect or even constant across categories to be compared. Therefore, monitoring programs should correct for species detectability.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Basic and Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1078/1439-1791-00194","collaboration":"6127_Kery.pdf","usgsCitation":"Kery, M., and Schmid, H., 2004, Monitoring programs need to take into account imperfect species detectability: Basic and Applied Ecology, v. 5, no. 1, p. 65-73, https://doi.org/10.1078/1439-1791-00194.","productDescription":"65-73","startPage":"65","endPage":"73","numberOfPages":"9","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":199446,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":17401,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://dx.doi.org/10.1078/1439-1791-00194","linkFileType":{"id":5,"text":"html"}}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db6358cf","contributors":{"authors":[{"text":"Kery, M.","contributorId":46637,"corporation":false,"usgs":true,"family":"Kery","given":"M.","affiliations":[],"preferred":false,"id":341175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmid, Hans","contributorId":19648,"corporation":false,"usgs":true,"family":"Schmid","given":"Hans","affiliations":[],"preferred":false,"id":341174,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5224303,"text":"5224303 - 2004 - Investigating species co-occurrence patterns when species are detected imperfectly","interactions":[],"lastModifiedDate":"2021-08-30T15:42:59.828089","indexId":"5224303","displayToPublicDate":"2010-06-16T12:18:50","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Investigating species co-occurrence patterns when species are detected imperfectly","docAbstract":"1. Over the last 30 years there has been a great deal of interest in investigating patterns of species co-occurrence across a number of locations, which has led to the development of numerous methods to determine whether there is evidence that a particular pattern may not have occurred by random chance. 2. A key aspect that seems to have been largely overlooked is the possibility that species may not always be detected at a location when present, which leads to 'false absences' in a species presence/absence matrix that may cause incorrect inferences to be made about co-occurrence patterns. Furthermore, many of the published methods for investigating patterns of species co-occurrence do not account for potential differences in the site characteristics that may partially (at least) explain non-random patterns (e.g. due to species having similar/different habitat preferences). 3. Here we present a statistical method for modelling co-occurrence patterns between species while accounting for imperfect detection and site characteristics. This method requires that multiple presence/absence surveys for the species be conducted over a reasonably short period of time at most sites. The method yields unbiased estimates of probabilities of occurrence, and is practical when the number of species is small (< 4). 4. To illustrate the method we consider data collected on two terrestrial salamander species, Plethodon jordani and members of the Plethodon glutinosus complex, collected in the Great Smoky Mountains National Park, USA. We find no evidence that the species do not occur independently at sites once site elevation has been allowed for, although we find some evidence of a statistical interaction between species in terms of detectability that we suggest may be due to changes in relative abundances.
","language":"English","publisher":"Wiley","doi":"10.1111/j.0021-8790.2004.00828.x","usgsCitation":"MacKenzie, D., Bailey, L., and Nichols, J., 2004, Investigating species co-occurrence patterns when species are detected imperfectly: Journal of Animal Ecology, v. 73, no. 3, p. 546-555, https://doi.org/10.1111/j.0021-8790.2004.00828.x.","productDescription":"10 p.","startPage":"546","endPage":"555","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":477994,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.0021-8790.2004.00828.x","text":"Publisher Index Page"},{"id":199464,"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":"73","issue":"3","noUsgsAuthors":false,"publicationDate":"2004-04-16","publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699fe6","contributors":{"authors":[{"text":"MacKenzie, D.I.","contributorId":69522,"corporation":false,"usgs":true,"family":"MacKenzie","given":"D.I.","email":"","affiliations":[],"preferred":false,"id":341203,"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":341202,"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":341201,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":5224609,"text":"5224609 - 2004 - Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation","interactions":[],"lastModifiedDate":"2017-07-25T15:51:07","indexId":"5224609","displayToPublicDate":"2010-06-16T12:18:39","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation","docAbstract":"Life history theory and associated empirical generalizations predict that population growth rate (λ) in long-lived animals should be most sensitive to adult survival; the rates to which λ is most sensitive should be those with the smallest temporal variances; and stochastic environmental events should most affect the rates to which λ is least sensitive. To date, most analyses attempting to examine these predictions have been inadequate, their validity being called into question by problems in estimating parameters, problems in estimating the variability of parameters, and problems in measuring population sensitivities to parameters. We use improved methodologies in these three areas and test these life-history predictions in a population of red-tailed tropicbirds (Phaethon rubricauda). We support our first prediction that λ is most sensitive to survival rates. However the support for the second prediction that these rates have the smallest temporal variance was equivocal. Previous support for the second prediction may be an artifact of a high survival estimate near the upper boundary of 1 and not a result of natural selection canalizing variances alone. We did not support our third prediction that effects of environmental stochasticity (El Niño) would most likely be detected in vital rates to which λ was least sensitive and which are thought to have high temporal variances. Comparative data-sets on other seabirds, within and among orders, and in other locations, are needed to understand these environmental effects.
","language":"English","publisher":"Wiley","doi":"10.1111/j.0030-1299.2004.13119.x","usgsCitation":"Doherty, P., Schreiber, E., Nichols, J., Hines, J., Link, W., Schenk, G., and Schreiber, R., 2004, Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation: Oikos, v. 105, no. 3, p. 606-618, https://doi.org/10.1111/j.0030-1299.2004.13119.x.","productDescription":"13 p.","startPage":"606","endPage":"618","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201992,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"3","noUsgsAuthors":false,"publicationDate":"2004-05-14","publicationStatus":"PW","scienceBaseUri":"4f4e4ac8e4b07f02db67bc52","contributors":{"authors":[{"text":"Doherty, P.F. Jr.","contributorId":74096,"corporation":false,"usgs":true,"family":"Doherty","given":"P.F.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":342067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreiber, E.A.","contributorId":84472,"corporation":false,"usgs":true,"family":"Schreiber","given":"E.A.","email":"","affiliations":[],"preferred":false,"id":342068,"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":342064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":342065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":342063,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schenk, G.A.","contributorId":37446,"corporation":false,"usgs":true,"family":"Schenk","given":"G.A.","email":"","affiliations":[],"preferred":false,"id":342066,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schreiber, R.W.","contributorId":92782,"corporation":false,"usgs":true,"family":"Schreiber","given":"R.W.","email":"","affiliations":[],"preferred":false,"id":342069,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":5224614,"text":"5224614 - 2004 - Modeling abundance effects in distance sampling","interactions":[],"lastModifiedDate":"2021-11-29T15:57:28.992797","indexId":"5224614","displayToPublicDate":"2010-06-16T12:18:39","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling abundance effects in distance sampling","docAbstract":"Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective of such studies is to evaluate the relationship between abundance or density and covariates that describe animal habitat or other environmental influences. However, little attention has been focused on methods of modeling abundance covariate effects in conventional distance-sampling models. In this paper we propose a distance-sampling model that accommodates covariate effects on abundance. The model is based on specification of the distance-sampling likelihood at the level of the sample unit in terms of local abundance (for each sampling unit). This model is augmented with a Poisson regression model for local abundance that is parameterized in terms of available covariates. Maximum-likelihood estimation of detection and density parameters is based on the integrated likelihood, wherein local abundance is removed from the likelihood by integration. We provide an example using avian point-transect data of Ovenbirds (Seiurus aurocapillus) collected using a distance-sampling protocol and two measures of habitat structure (understory cover and basal area of overstory trees). The model yields a sensible description (positive effect of understory cover, negative effect on basal area) of the relationship between habitat and Ovenbird density that can be used to evaluate the effects of habitat management on Ovenbird populations.
","language":"English","publisher":"Wiley","doi":"10.1890/03-3127","usgsCitation":"Royle, J., Dawson, D., and Bates, S., 2004, Modeling abundance effects in distance sampling: Ecology, v. 85, no. 6, p. 1591-1597, https://doi.org/10.1890/03-3127.","productDescription":"7 p.","startPage":"1591","endPage":"1597","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":203204,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Frederick County","otherGeospatial":"Catoctin Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.5579833984375,\n 39.457402514270825\n ],\n [\n -77.40692138671875,\n 39.457402514270825\n ],\n [\n -77.40692138671875,\n 39.68605343225986\n ],\n [\n -77.5579833984375,\n 39.68605343225986\n ],\n [\n -77.5579833984375,\n 39.457402514270825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a29e4b07f02db611c93","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":342091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dawson, D.K. 0000-0001-7531-212X","orcid":"https://orcid.org/0000-0001-7531-212X","contributorId":94752,"corporation":false,"usgs":true,"family":"Dawson","given":"D.K.","affiliations":[],"preferred":false,"id":342090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bates, S.","contributorId":44271,"corporation":false,"usgs":true,"family":"Bates","given":"S.","email":"","affiliations":[],"preferred":false,"id":342089,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":5224776,"text":"5224776 - 2004 - Mortality of Mississippi Sandhill Crane chicks","interactions":[],"lastModifiedDate":"2018-02-06T12:54:09","indexId":"5224776","displayToPublicDate":"2010-06-16T12:18:39","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2191,"text":"Journal of Avian Medicine and Surgery","active":true,"publicationSubtype":{"id":10}},"title":"Mortality of Mississippi Sandhill Crane chicks","docAbstract":"Mississippi sandhill cranes (Grus canadensis pulla) are a highly endangered species that live in the wild in 1 county in Mississippi. As part of a large effort to restore these endangered cranes, we are conducting a project to look at the causes of mortality in crane chicks on the Mississippi Sandhill Crane National Wildlife Refuge in Gautier, MS, USA. This includes surgically implanting miniature radio transmitters in crane chicks to gather data on mortality. This article describes some of the practical difficulties in conducting this type of project in a savannah and swamp location along the Gulf Coast of the USA.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Avian Medicine and Surgery","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","usgsCitation":"Olsen, G.H., 2004, Mortality of Mississippi Sandhill Crane chicks: Journal of Avian Medicine and Surgery, v. 18, no. 4, p. 269-272.","productDescription":"269-272","startPage":"269","endPage":"272","numberOfPages":"4","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":196196,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":17091,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://www.bioone.org/perlserv/?request=get-abstract&doi=10.1647%2F1082-6742(2004)018[0269%3AMOMSCC]2.0.CO%3B2","linkFileType":{"id":5,"text":"html"}}],"volume":"18","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b4785","contributors":{"authors":[{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":342648,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":5224395,"text":"5224395 - 2004 - Estimation of sex-specific survival from capture-recapture data when sex is not always known","interactions":[],"lastModifiedDate":"2021-08-13T16:05:38.772379","indexId":"5224395","displayToPublicDate":"2010-06-16T12:18:36","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of sex-specific survival from capture-recapture data when sex is not always known","docAbstract":"Many animals lack obvious sexual dimorphism, making assignment of sex difficult even for observed or captured animals. For many such species it is possible to assign sex with certainty only at some occasions; for example, when they exhibit certain types of behavior. A common approach to handling this situation in capture-recapture studies has been to group capture histories into those of animals eventually identified as male and female and those for which sex was never known. Because group membership is dependent on the number of occasions at which an animal was caught or observed (known sex animals, on average, will have been observed at more occasions than unknown-sex animals), survival estimates for known-sex animals will be positively biased, and those for unknown animals will be negatively biased. In this paper, we develop capture-recapture models that incorporate sex ratio and sex assignment parameters that permit unbiased estimation in the face of this sampling problem. We demonstrate the magnitude of bias in the traditional capture-recapture approach to this sampling problem, and we explore properties of estimators from other ad hoc approaches. The model is then applied to capture-recapture data for adult Roseate Terns (Sterna dougallii) at Falkner Island, Connecticut, 1993-2002. Sex ratio among adults in this population favors females, and we tested the hypothesis that this population showed sex-specific differences in adult survival. Evidence was provided for higher survival of adult females than males, as predicted. We recommend use of this modeling approach for future capture-recapture studies in which sex cannot always be assigned to captured or observed animals. We also place this problem in the more general context of uncertainty in state classification in multistate capture-recapture models.
","language":"English","publisher":"Wiley","doi":"10.1890/03-0578","usgsCitation":"Nichols, J., Kendall, W., Hines, J., and Spendelow, J., 2004, Estimation of sex-specific survival from capture-recapture data when sex is not always known: Ecology, v. 85, no. 12, p. 3192-3201, https://doi.org/10.1890/03-0578.","productDescription":"10 p.","startPage":"3192","endPage":"3201","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201913,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Falkner Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.65443325042725,\n 41.21288373722492\n ],\n [\n -72.65529155731201,\n 41.21217349004246\n ],\n [\n -72.65477657318114,\n 41.21152780409429\n ],\n [\n -72.65529155731201,\n 41.21052697828058\n ],\n [\n -72.65408992767334,\n 41.21059154814995\n ],\n [\n -72.65318870544434,\n 41.21152780409429\n ],\n [\n -72.65280246734618,\n 41.21201206915286\n ],\n [\n -72.65288829803467,\n 41.21327114152892\n ],\n [\n -72.6537036895752,\n 41.2136585435387\n ],\n [\n -72.65413284301756,\n 41.21352940979034\n ],\n [\n -72.65443325042725,\n 41.21288373722492\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ae4b07f02db5fb1fa","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":341541,"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":341542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":341543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spendelow, J. A. 0000-0001-8167-0898","orcid":"https://orcid.org/0000-0001-8167-0898","contributorId":72478,"corporation":false,"usgs":true,"family":"Spendelow","given":"J. A.","affiliations":[],"preferred":false,"id":341544,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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 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":5224435,"text":"5224435 - 2004 - Abundance estimation and conservation biology","interactions":[],"lastModifiedDate":"2016-10-27T12:06:27","indexId":"5224435","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":"Abundance estimation and conservation biology","docAbstract":"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":5224308,"text":"5224308 - 2004 - Contaminant exposure and reproductive success of Ospreys (Pandion haliaetus) nesting in Chesapeake Bay regions of concern","interactions":[],"lastModifiedDate":"2016-08-26T14:02:22","indexId":"5224308","displayToPublicDate":"2010-06-16T12:13:21","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Contaminant exposure and reproductive success of Ospreys (Pandion haliaetus) nesting in Chesapeake Bay regions of concern","docAbstract":"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. 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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":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":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":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":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"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}]}} ]}