Biometrics Completed
Mathematical and statistical methods used to analyze biological data are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of ecological systems. Through the development of specialized and sophisticated quantitative tools and models, the complex nature of data arising from studies of ecological systems can be understood.
Scientist conduct research to develop and evaluate mathematical and statistical tools and models that abstract and accommodate the unique characteristics of ecological systems and data, while also allowing for maximum extraction of information about those systems. This research is critical for improving the information gained from time-consuming, logistically diffi cult, and resource-intense field studies.
Using Quantile Regression to Investigate Ecological Limiting Factors - Principal Investigator - Brian Cade
Unexplained heterogeneity in statistical models of animal responses to their physical environment is reasonable to expect because the measured habitat resources are a constraint on—but not the sole determinant of—abundance, survival, fecundity, or fitness. The ecological understanding and reliability of management predictions based on animal habitat models can be improved by shifting focus from estimating expected values (means) of responses to estimating intervals of responses associated with multiple percentiles of a distribution.
Quantitative and Statistical Research Collaboration - Principal Investigator - Brian Cade
Mathematical and statistical models are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of complicated ecological systems, including developing mechanistic hypotheses pertaining to ecological systems, designing studies that elucidate ecosystem structure and function, and extracting information from data.
Below are other science projects associated with this project.
Using Quantile Regression to Investigate Ecological Limiting Factors
Quantitative and Statistical Research Collaboration
Below are publications associated with this project.
Trophic magnification of organic chemicals: A global synthesis
Model averaging and muddled multimodel inferences
A plan for the North American Bat Monitoring Program (NABat)
Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know
Daily nest survival rates of Gunnison Sage-Grouse (Centrocercus minimus): assessing local- and landscape-scale drivers
Associations of wintering birds with habitat in semidesert and plains grasslands in Arizona
Variability in seroprevalence of rabies virus neutralizing antibodies and associated factors in a Colorado population of big brown bats (Eptesicus fuscus)
Estimating risks to aquatic life using quantile regression
Quantile equivalence to evaluate compliance with habitat management objectives
Estimating equivalence with quantile regression
Trophic magnification of PCBs and its relationship to the octanol-water partition coefficient
Assessing conservation relevance of organism-environment relations using predicted changes in response variables
- Overview
Mathematical and statistical methods used to analyze biological data are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of ecological systems. Through the development of specialized and sophisticated quantitative tools and models, the complex nature of data arising from studies of ecological systems can be understood.
Scientist conduct research to develop and evaluate mathematical and statistical tools and models that abstract and accommodate the unique characteristics of ecological systems and data, while also allowing for maximum extraction of information about those systems. This research is critical for improving the information gained from time-consuming, logistically diffi cult, and resource-intense field studies.
Using Quantile Regression to Investigate Ecological Limiting Factors - Principal Investigator - Brian Cade
Unexplained heterogeneity in statistical models of animal responses to their physical environment is reasonable to expect because the measured habitat resources are a constraint on—but not the sole determinant of—abundance, survival, fecundity, or fitness. The ecological understanding and reliability of management predictions based on animal habitat models can be improved by shifting focus from estimating expected values (means) of responses to estimating intervals of responses associated with multiple percentiles of a distribution.
Quantitative and Statistical Research Collaboration - Principal Investigator - Brian Cade
Mathematical and statistical models are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of complicated ecological systems, including developing mechanistic hypotheses pertaining to ecological systems, designing studies that elucidate ecosystem structure and function, and extracting information from data.
- Science
Below are other science projects associated with this project.
Using Quantile Regression to Investigate Ecological Limiting Factors
Unexplained heterogeneity in statistical models of animal responses to their physical environment is reasonable to expect because the measured habitat resources are a constraint on—but not the sole determinant of—abundance, survival, fecundity, or fitness. The ecological understanding and reliability of management predictions based on animal habitat models can be improved by shifting focus from...Quantitative and Statistical Research Collaboration
Mathematical and statistical models are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of complicated ecological systems, including developing mechanistic hypotheses pertaining to ecological systems, designing studies that elucidate ecosystem structure and function, and extracting information from data. - Publications
Below are publications associated with this project.
Trophic magnification of organic chemicals: A global synthesis
Production of organic chemicals (OCs) is increasing exponentially, and some OCs biomagnify through food webs to potentially toxic levels. Biomagnification under field conditions is best described by trophic magnification factors (TMFs; per trophic level change in log-concentration of a chemical) which have been measured for more than two decades. Syntheses of TMF behavior relative to chemical traiAuthorsDavid Walters, T.D. Jardine, Brian S. Cade, K.A. Kidd, D.C.G. Muir, Peter C. Leipzig-ScottModel averaging and muddled multimodel inferences
Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial eAuthorsBrian S. CadeA plan for the North American Bat Monitoring Program (NABat)
The purpose of the North American Bat Monitoring Program (NABat) is to create a continent-wide program to monitor bats at local to rangewide scales that will provide reliable data to promote effective conservation decisionmaking and the long-term viability of bat populations across the continent. This is an international, multiagency program. Four approaches will be used to gather monitoring dataAuthorsSusan C. Loeb, Thomas J. Rodhouse, Laura E. Ellison, Cori L. Lausen, Jonathan D. Reichard, Kathryn M. Irvine, Thomas E. Ingersoll, Jeremy T. H. Coleman, Wayne E. Thogmartin, John R. Sauer, Charles M. Francis, Mylea L. Bayless, Thomas R. Stanley, Douglas H. JohnsonAssessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know
Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. GeologAuthorsZachary H. Bowen, Gretchen P. Oelsner, Brian S. Cade, Tanya J. Gallegos, Aïda M. Farag, David N. Mott, Christopher J. Potter, Peter J. Cinotto, Melanie L. Clark, William M. Kappel, Timothy M. Kresse, Cynthia P. Melcher, Suzanne Paschke, David D. Susong, Brian A. VarelaByEcosystems Mission Area, Water Resources Mission Area, Energy Resources Program, Central Energy Resources Science Center, Colorado Water Science Center, Columbia Environmental Research Center, Fort Collins Science Center, Geology, Energy & Minerals Science Center, John Wesley Powell Center for Analysis and Synthesis, Lower Mississippi-Gulf Water Science Center, New Mexico Water Science Center, New York Water Science Center, Ohio-Kentucky-Indiana Water Science Center, Oklahoma-Texas Water Science Center, Utah Water Science Center, Wyoming-Montana Water Science CenterDaily nest survival rates of Gunnison Sage-Grouse (Centrocercus minimus): assessing local- and landscape-scale drivers
The Gunnison Sage-Grouse (Centrocercus minimus) is a species of conservation concern and is a candidate for listing under the U.S. Endangered Species Act because of substantial declines in populations from historic levels. It is thought that loss, fragmentation, and deterioration of sagebrush (Artemisia spp.) habitat have contributed to the decline and isolation of this species into seven geographAuthorsThomas R. Stanley, Cameron L. Aldridge, Joanne Saher, Theresa ChildersAssociations of wintering birds with habitat in semidesert and plains grasslands in Arizona
We studied associations with winter habitat for seven species of birds, one species-group (eastern and western meadowlarks combined), and total sparrows at seven sites in the semidesert and plains grasslands of southeastern Arizona from 1999–2001, sampling with mist-nets and survey-transects. We measured structure and composition of vegetation, assessing vegetative differences among sites, and modAuthorsJanet M. Ruth, Thomas R. Stanley, Caleb E. GordonVariability in seroprevalence of rabies virus neutralizing antibodies and associated factors in a Colorado population of big brown bats (Eptesicus fuscus)
In 2001–2005 we sampled permanently marked big brown bats (Eptesicus fuscus) at summer roosts in buildings at Fort Collins, Colorado, for rabies virus neutralizing antibodies (RVNA). Seroprevalence was higher in adult females (17.9%, n = 2,332) than males (9.4%, n = 128; P = 0.007) or volant juveniles (10.2%, n = 738; PAuthorsThomas J. O’Shea, Richard A. Bowen, Thomas R. Stanley, Vidya Shankar, Charles E. RupprechtEstimating risks to aquatic life using quantile regression
One of the primary goals of biological assessment is to assess whether contaminants or other stressors limit the ecological potential of running waters. It is important to interpret responses to contaminants relative to other environmental factors, but necessity or convenience limit quantification of all factors that influence ecological potential. In these situations, the concept of limiting factAuthorsTravis S. Schmidt, William H. Clements, Brian S. CadeQuantile equivalence to evaluate compliance with habitat management objectives
Equivalence estimated with linear quantile regression was used to evaluate compliance with habitat management objectives at Arapaho National Wildlife Refuge based on monitoring data collected in upland (5,781 ha; n = 511 transects) and riparian and meadow (2,856 ha, n = 389 transects) habitats from 2005 to 2008. Quantiles were used because the management objectives specified proportions of theAuthorsBrian S. Cade, Pamela R. JohnsonEstimating equivalence with quantile regression
Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero. Equivalence tests and confidence interval estimates are based on a null hypothesis that a parameter estimAuthorsB.S. CadeTrophic magnification of PCBs and its relationship to the octanol-water partition coefficient
We investigated polychlorinated biphenyl (PCB) bioaccumulation relative to octanol-water partition coefficient (KOW) and organism trophic position (TP) at the Lake Hartwell Superfund site (South Carolina). We measured PCBs (127 congeners) and stable isotopes (??15N) in sediment, organic matter, phytoplankton, zooplankton, macroinvertebrates, and fish. TP, as calculated from ??15N, was significantlAuthorsD.M. Walters, M.A. Mills, B.S. Cade, L.P. BurkardAssessing conservation relevance of organism-environment relations using predicted changes in response variables
1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predicAuthorsKevin J. Gutzwiller, Wylie C. Barrow, Joseph D. White, Lori Johnson-Randall, Brian S. Cade, Lisa M. Zygo