A biostatistician with 30 years of experience

HINRICHSEN ENVIRONMENTAL SERVICES

Services
Biostatistics Consulting 
Over the past 30 years Hinrichsen has developed juvenile salmon passage models, life-cycle models, population viability models, and conducted detailed analyses of spawner-recruit models to estimate passage mortality and latent mortality. He has conducted a priori power analyses for evaluating experimental management and experiments aimed at estimating relative reproductive success of hatchery-born spawners in the wild. 

Population Viability Analysis 
Population growth rate, variance, autocorrelation, and population abundance are used to estimate extinction risks of endangered salmon populations. Population viability analysis is performed on several populations simultaneously to increase statistical accuracy and model synchrony in related populations. Effects of measurement error are considered in a state-space modeling approach. 

Research, Monitoring, and Evaluation 
Designs of experiments for estimating effects of habitat action are evaluated. Tagging programs are designed for monitoring adult escapement, survival, migration timing, and distribution. Power analysis tools are developed to determine appropriate tagging numbers for measuring smolt-to-adult ratios, downstream survival, adult escapement, survival, timing and distribution. Alternative statistical methods for estimating escapement are evaluated. Several statistical tools for research, monitoring, and evaluations may be found here (on my github page).

Population Viability Analysis
Population growth rate, variance,
autocorrelation, and population abundance are
used to estimate extinction risks of
endangered salmon populations. Population
viability analysis is performed on several
populations simultaneously to increase
statistical accuracy and model synchrony in
related populations. Effects of measurement
error are considered in a state-space modeling
approach.
Hinrichsen, R.A. 2009. Population viability
analysis for several populations using
multivariate state-space models. Ecological
Modelling 220: 1197-1202.
Hinrichsen, R. A. and E. E. Holmes. 2009.
Using multivariate state-space models to
study spatial structure and dynamics. In
Spatial Ecology (editors Robert Stephen
Cantrell, Chris Cosner, Shigui Ruan).
CRC/Chapman Hall.