Threatened and endangered species and our wildlife legacy

Threatened and endangered species face a multitude of threats. While habitat conservation, legal protection, restoration and other professional measures seek to minimize impacts of threats to sensitive species, some threats arise quickly and result in urgent managerial challenges. Here, we focus on the rapidly emerging threat of predation to sensitive prey species by rapidly expanding populations of common ravens. 

Population matrix models have long been used to identify managerial activities to slow, stem, or reverse undesirable population growth of subsidized predators. We leveraged the mathematics of a matrix model to develop interactive computational tools that aid managers in identifying methods to restore predator-prey ratios to sustainable levels. 

StallPOPdV4: Reduction in growth for any 3-stage species through 1-, 2-, or 3-way treatments 

V4 provides a user-friendly interface that enables the exploration of population control to any three-stage species when all treatment types are considered. 

Access the preliminary results of StallPOPdV4 Software5

Access StallPOPdV4

 

 

Earlier Versions of the StallPOPd Software: 

StallPOPdV3: Reduction in growth of ravens through 1-, 2-, or 3-way treatments 

V3 can be used to pinpoint combinations of treatments to control the undesirable growth of common ravens. 

StallPOPdV2: Reduction in growth of raven via the destruction of eggs and culling of live individuals

V2 allows the user to explore how the destruction of eggs can compliment the culling of live individuals in activities designed to control the undesirable growth of common ravens. 

StallPOPd: Reduction in growth of raven via the destruction of eggs

V1 provides an avenue to explore growth equations of common raven when eggs are destroyed. 

Note: All capabilities of V1-V3 are embedded in V4. However, you may download earlier versions by visiting the dois listed in the "Preferred Citations" accordion. 

 

Acknowledgments

We thank Jennifer Peaslee, Cara Them, Alyssa Kaganer and three anonymous reviewers for helpful suggestions. The findings and conclusions in these materials are those of the authors(s) and do not necessarily represent the views of the U.S. Fish and Wildlife Service (USFWS) nor the U.S. Geological Survey (USGS). 

 

Although the StallPOPd software can aid in the exploration of treatment alternatives, it is not appropriate for isolated use. 

The software computes treatment targets through the limited perspective of deterministic population modeling, and the mathematics hinge on several simplifying assumptions.

The math *does not* consider:

  1. Carrying capacity,
  2. Genetics,
  3. Sex ratio,
  4. Behavior,
  5. Any type of variation or stochastic noise (demographic, environmental, sampling),
  6. Weather, climate, or seasonality,
  7. Competition with other species,
  8. Dispersal,
  9. Predators.

This app reduces the expression of population growth into its skeletal mathematical components and investigates their relationships in a closed system. However, ecology does not operate in a vacuum. It is prudent to simultaneously assess management alternatives from all other important ecological perspectives prior to enacting any given treatment.

This software was created as an auxiliary tool for the research entitled: 

1aShields, T., Currylow, A., Hanley, B., Boland, S., Boarman, W., & M. Vaughn. 2019. Novel management tool for subsidized avian predators: a case study in the conservation of a threatened species. Ecosphere. doi: https://doi.org/10.1002/ecs2.2895

1bHanley, B., Currylow, A., Holcomb, K., Shields, T., Boland, S., Boarman, W., & Vaughn, M. Identifying population management strategies for avian predators: a decision tool. In peer revision.

Preferred citation for use of the software:

2Shields, T., Currylow, A., Hanley, B., Boland, S., Boarman, W., & Vaughn, M. 2019. StallPOPd: Applied Population Modeling for Halting the Growth of a Subsidized Avian Predator [Software]. Cornell University Library eCommons Repository. doi: https://doi.org/10.7298/sk2e-0c38

3Hanley, B., Currylow, A., Holcomb, K., Shields, T., Boland, S.,  Boarman, W., & Vaughn, M. 2020. StallPOPd V2 Web Interactive: Interactive software to calculate the combination of egg addling and bird culling needed to stall or halt population growth of subsidized ravens [Software]. doi: https://doi.org/10.7298/sk2e-0c38.2

4Hanley, B., Currylow, A., Holcomb, K., Shields, T., Boland, S.,  Boarman, W., & Vaughn, M. 2020. StallPOPd V3 Web Interactive: Interactive software to calculate the combination of egg addling and bird culling needed to stall or halt population growth of subsidized ravens [Software]. doi: https://doi.org/10.7298/sk2e-0c38.3

5Hanley, B., Currylow, A., Holcomb, K., Shields, T., Boland, S.,  Boarman, W., & Vaughn, M. 2021. StallPOPdV4 Web Interactive: Software to compute population control treatments of a subsidized predator [Software]. doi: https://doi.org/10.7298/sk2e-0c38.4

 

Mathematical references

Caswell, H., 2001. Matrix population models: construction, analysis, and interpretation, 2 ed. Sinauer Associates, Inc, Sunderland, Massachusetts, USA.

de Kroon, H., van Groenendael, J., Ehrlén, J., 2000. Elasticities: A review of methods and model limitations. Ecology, 81, 607–618.

Hanley, B.J., Dennis, B.C., 2019. Analytical expressions for the eigenvalues, demographic quantities, and extinction criteria arising from a three-stage wildlife population matrix. Natural Resource Modelling.  

Kristan, W.B., Boarman, W.I., Webb, W.C., 2005. Stage-structured matrix models of Common Ravens (Corvus corax) in the west Mojave Desert, CA US Geological Survey, Department of the Interior.

Lefkovitch, L.P. (1965).  The study of population growth in organism groups by stages. Biometrics, 21, 1-18. 

Leslie, P.H. (1945).  On the use of matrices in certain population mathematics. Biometrika, 33, 183-212.  

Tuljapurkar, S. (2008). Stable population theory. The New Palgrave Dictionary of Economics. 2nd Edition. (eds). Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan, United Kingdom.

Software references

R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.  

R Shiny.  (2018). Shiny.  Web Application Framework for R.  

RStudio Team. (2015). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA 

We’d also like to thank the R online user community (eg. several anonymous coders, Matthew Plourde) for providing example code and insight on programming around various obstacles (e.g. https://stackoverflow.com/questions/25455154/navlistpanel-make-tabs-sequ...).