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.
The complex nature of ecological systems and the data arising from studies of these systems often require the development of specialized and sophisticated models so that progress can be made in understanding these systems. The objective under this task is to develop mathematical or statistical models that abstract and accommodate the unique characteristics of ecological systems and data, while allowing for maximum extraction of information about those systems. This is accomplished through collaboration with field biologists having unique or unusual data analysis questions or circumstances, and with mathematicians and statisticians able to creatively apply powerful mathematical or statistical methods to difficult, real-world problems.
Below are other science projects associated with this project.
Using Quantile Regression to Investigate Ecological Limiting Factors
Below are publications associated with this project.
Model averaging and muddled multimodel inferences
Daily nest survival rates of Gunnison Sage-Grouse (Centrocercus minimus): assessing local- and landscape-scale drivers
Breeding biology of an afrotropical forest understory bird community in northeastern Tanzania
Genetic diversity and species diversity of stream fishes covary across a land-use gradient
Sagebrush ecosystem conservation and management: Ecoregional assessment tools and models for the Wyoming Basins
Foaling rates in feral horses treated with the immunocontraceptive porcine zona pellucida
Trophic magnification of PCBs and its relationship to the octanol-water partition coefficient
Genetic and environmental influences on leaf phenology and cold hardiness of native and introduced riparian trees
Chapter 6: Detectability adjusted count models of songbird abundance
Habitat fragmentation reduces nest survival in an Afrotropical bird community in a biodiversity hotspot
Assessing conservation relevance of organism-environment relations using predicted changes in response variables
Influences of immunocontraception on time budgets, social behavior, and body condition in feral horses
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.
The complex nature of ecological systems and the data arising from studies of these systems often require the development of specialized and sophisticated models so that progress can be made in understanding these systems. The objective under this task is to develop mathematical or statistical models that abstract and accommodate the unique characteristics of ecological systems and data, while allowing for maximum extraction of information about those systems. This is accomplished through collaboration with field biologists having unique or unusual data analysis questions or circumstances, and with mathematicians and statisticians able to creatively apply powerful mathematical or statistical methods to difficult, real-world problems.
Below are other science projects associated with this project.
Using Quantile Regression to Investigate Ecological Limiting Factors
Below are publications associated with this project.