Prioritizing Habitats within Iowa to Manage for Priority SGCN


Principal Investigator: 

Zhengyuan Zhu

Student Investigator: 

Xiaodan Lyu


Karen E. Kinkead (Iowa DNR),

Stephen J. Dinsmore (NREM),

Kevin T. Murphy (NREM),

Tyler M. Harms (CSSM),

Steven Roberts (CSSM)


1 October 2015 – 30 June 2016

Funding Source(s): 

U.S. Fish and Wildlife Service

Goals and Objectives:

The objectives of this project were as follows:

  • Use the Multiple Species Inventory and Monitoring (MSIM) Program occupancy models to create predictive species maps for priority Species of Greatest Conservation Need (SGCN).
  • Create an occurrence layer showing the areas (based upon landscape variables) in Iowa that are predicted to have the highest density of SGCN.


The Iowa Comprehensive Wildlife Action Plan was completed in 2005 as a guide for management of wildlife and their habitats across the state and was recently revised with the use of updated information.  The Plan not only focuses on “keeping common species common” but also identifies Species of Greatest Conservation Need (SGCN).  In an effort to gather more information on all wildlife in Iowa, particularly SGCN, the Iowa Department of Natural Resources (Iowa DNR) and Iowa State University designed and implemented the Multiple Species Inventory and Monitoring (MSIM) Program in 2006.  This program annually conducts standardized surveys for wildlife species of nine taxonomic groups on public properties across Iowa.  The Iowa DNR partnered with the Center for Survey Statistics and Methodology (CSSM) at Iowa State University to develop predictive occurrence maps for SGCN using data from the MSIM Program as an effort to prioritize areas of conservation action for SGCN. 

Using species occurrence data for 291 sites surveyed as part of the MSIM program from 2006 – 2014, we evaluated the influence of landscape habitat characteristics on the probability of occupancy and probability of colonization for 59 SGCN using robust design occupancy models in Program MARK.  Using the habitat covariate from the best model for each SGCN and estimated habitat characteristics for all of Iowa, we developed a predictive map of both probability of occupancy and colonization for each SGCN.


Conclusions and Recommendations:

An interactive web application was developed to display predictive maps and parameter estimates for each SGCN.  This web application will be available to researchers and managers across Iowa to aid in focusing conservation efforts for SGCN.  We also developed occurrence layers for each taxonomic group (e.g., birds) that displays areas of highest density of SGCN.  All predictive models tested with acceptable levels of accuracy.

The web application will be hosted by CSSM for use by researchers and managers for 1-2 years. 

10/01/2015 to 06/30/2016