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Jamie S. Sanderlin

Jamie Sanderlin

Research Wildlife Biologist (Quantitative Vertebrate Ecologist)

Address: 
2500 South Pine Knoll Drive
Flagstaff, AZ 86001
Phone: 
928-556-2182
Contact Jamie S. Sanderlin

Current Research

  • Evaluating fire effects on bird and small mammal communities
  • Developing sampling designs and optimizing resources for monitoring programs
  • Developing Bayesian hierarchical models to evaluate wildlife population and community dynamics
  • Using citizen science to monitor wildlife populations and communities
  • Developing methods and sampling designs for combining multiple data sources (data integration)
  • Assessing large-scale effects of wildfire and climate change on bird and vegetation communities in the Sky Islands, Arizona
  • Wildlife genomics and bioinformatics of greater sage-grouse
  • Lifetime reproductive success of northern goshawks

Research Interests

  • Population and community dynamics
  • Wildlife genomics and bioinformatics
  • Bayesian statistics and hierarchical models
  • Data integration
  • Mark-recapture and occupancy models with ecological applications
  • Cost-effective sampling designs
  • Modeling genotyping error with genetic mark-recapture studies
  • Utilizing citizen science within monitoring programs

Past Research

Jamie Sanderlin worked on several quantitative projects before joining the USDA Forest Service, including:

  • Developed a Bayesian statistical model to call SNP genotypes using Next Generation Sequencing technology for inference on New Zealand sheep SNP discovery
  • Developed a Bayesian state-space model to estimate population abundance, survival, and recruitment from molecular parentage data
  • Ph.D. Dissertation in Wildlife Ecology and Management: Integrated demographic modeling and estimation of the central Georgia, USA, black bear population
  • M.S. Statistics Thesis: Misidentification error in non-invasive genetic mark-recapture sampling: case study with the central Georgia black bear population
  • Honors Thesis: Modeling patterns of dispersal in banner-tailed kangaroo rats, Dipodomys spectabilis, using capture-recapture data with the multi-strata, robust design

Why This Research is Important

Innovative quantitative approaches are needed to study wildlife species, especially species of special concern for National Forest Systems, since these species often occur at low densities and within patchy distributions. Jamie Sanderlin develops analytical applications for several collaborative projects in the realm of quantitative ecology, statistics, and bioinformatics.

Education

  • University of Georgia, Ph.D., Wildlife Ecology and Management, 2009
  • University of Georgia, M.S., Statistics, 2009
  • Purdue University, B.S., Ecology, Evolutionary, and Population Biology, 2002
  • Professional Experience

    Post-doctoral Scientist (Quantitative Vertebrate Ecologist), Rocky Mountain Research Station, Wildlife and Terrestrial Ecosystems, USDA Forest Service
    2011 to 2014

    Post-doctoral Fellow, University of Otago, Department of Mathematics and Statistics
    2009 to 2011

    Featured Publications

    Publications

    Reynolds, Richard T.; Lambert, Jeffrey; Kay, Shannon L.; Sanderlin, Jamie S.; Bird, Benjamin J., 2019. Factors affecting lifetime reproduction, longterm territory-specific reproduction, and estimation of habitat quality in northern goshawks
    Sanderlin, Jamie S.; Block, William M.; Strohmeyer, Brenda E.; Saab, Victoria A.; Ganey, Joseph L., 2019. Precision gain versus effort with joint models using detection/non‐detection and banding data
    Miller, David A. W.; Pacifici, Krishna; Sanderlin, Jamie S.; Reich, Brian J., 2019. The recent past and promising future for data integration methods to estimate species’ distributions
    Sanderlin, Jamie S.; Block, William M.; Strohmeyer, Brenda E., 2016. Long-term post-wildfire correlates with avian community dynamics in ponderosa pine forests [Chapter J]
    Schwartz, Michael K.; Sanderlin, Jamie S.; Block, William M., 2015. Manage habitat, monitor species [Chapter 10]
    Stan, Amanda B.; Fule, Peter Z.; Ireland, Kathryn B.; Sanderlin, Jamie S., 2014. Modern fire regime resembles historical fire regime in a ponderosa pine forest on Native American land
    Sanderlin, Jamie S.; Block, William M.; Ganey, Joseph L.; Iniguez, Jose, 2013. Preliminary assessment of species richness and avian community dynamics in the Madrean Sky Islands, Arizona
    Sanderlin, Jamie S.; Lazar, Nicole; Conroy, Michael J.; Reeves, Jaxk, 2012. Cost-efficient selection of a marker panel in genetic studies
    A photograph of downed trees with mullein in the foreground, green coniferous trees behind the mullein, and mountains with snow in the background.
    Model development combining multiple data sources to leverage data source strengths and for improved parameter precision has increased, but with limited discussion on precision gain versus effort. Some data sources take more effort than others, thus knowing how much improvement is gained with these monitoring metrics is important for allocating samples on the landscape. Our framework allows research and monitoring programs to evaluate optimal use of limited funds when multiple data sources are available within the study design phase to meet study objectives.
    BBN_emblem.jpg – Birds and Burns Network emblem
    Researchers studied avian relationships with wildfire to evaluate forest fire and fuels management strategies. Specifically, they document regional differences associated with historical fire regime with implications for broadly implemented strategies aimed at reducing severe wildfire risk. The results suggest that avian-fire relationships differ regionally, and therefore the best management practices for conserving or restoring avian diversity likely differ with historical fire regime.
    Photo: LEWIS WOOD BERRIESem.jpg; caption – Lewis’s Woodpecker most frequently nests in relatively open, recently burned forests with large diameter snags.
    Increases in forest fires are expected with future changes in climate, allowing more opportunities for post-fire salvage logging. Forest managers are challenged with implementing post-fire management policies while concurrently meeting the requirements of existing laws and planning documents to maintain habitat for wildlife species associated with snags. Design criteria for post-fire salvage logging is needed to concurrently manage for economic benefits and wildlife habitat.
    High severity burned patch from the 2011 Horseshoe Two Fire in the Chiricahua Mountains, Arizona.
    This research evaluates the use of citizen science in a region with increased stress from ongoing drought and wildfires. Researchers show how it allows for inexpensive and statistically rigorous monitoring, and fosters greater local involvement in science and conservation. This information will be used to determine optimal protocols for a long-term monitoring plan. Inexpensive and statistically rigorous long-term monitoring fosters local involvement in science and conservation.
    Wildfire has long been an important and complex disturbance agent in forests dominated by ponderosa pine in the western United States. However, many recent fires have burned with increased severity across large, contiguous areas, resulting in vast expanses with no surviving overstory trees. Researchers are looking at regeneration rates inponderosa pine forests after high-severity fires and examining the spatial patterns and environmental conditions in affected areas to help managers anticipate natural recovery and plan for post-fire management activities.
    Rocky Mountain Research Station (RMRS) scientists have been at the forefront of efforts to understand the ecology of the threatened Mexican spotted owls (Strix occidentalis lucida) for more than 25 years. These scientists and their cooperators have produced most of the existing scientific information on this species. Today, RMRS scientists continue to be actively involved in developing new knowledge on this owl, synthesizing existing information, and working with managers to integrate habitat requirements for the owl and its important prey species into land management plans.
    We are integrating multiple datasets, statistical modeling tools, and simulation approaches to quantify habitat and predict population responses by woodpecker and other wildlife species of conservation concern to natural disturbance (wildfire, bark beetle outbreaks) and forest management activities to inform adaptive management of dry conifer forests.
    Bioinformatics and new statistical models for quantitative analyses using genetic and genomic data provide innovative approaches for the study of wildlife species, especially species of special concern for the U.S. National Forest System.
    Innovative quantitative approaches have been developed for evaluating wildfire and prescribed fire effects on wildlife communities in several western North American national forests.
    Numerous factors influence the establishment and growth of tree seedlings after high-severity wildfires. Understanding spatial patterns and environmental conditions influencing ponderosa pine and aspen regeneration post-wildfire can help managers monitor natural recovery.
    The avifauna within the Sky Islands of southeastern Arizona includes species found nowhere else in the United States. Rocky Mountain Research Station scientists initiated a study in the 1990s on avian distribution and habitat associations within the Sky Islands. This project involves monitoring vegetation and bird populations following wildfires, applying climate change models to assess potential changes and explore strategies for managing resilient forests and avian populations, and engaging citizens in data collection and long-term avian monitoring.