[Population Modeling] introduction

Thu Mar 9 03:55:54 PST 2017

I would like to introduce the population modeling work of my research 
group <http://life.bio.sunysb.edu/ee/akcakayalab/>.

We use population models with dynamic spatial structure to study the 
effects of climate and landscape changes on species.The novelty of our 
approach is that it links climate change models, ecological niche 
(species distribution or habitat suitability) models, and demographic 
models to predict the extinction risk of species under global 
change.The development of this coupled niche-population modeling 
approach was based on our previous work on metapopulation models with 
dynamic spatial structure [1], which were applied to simulate the 
effects of landscape changes resulting from timber harvest [2] and 
fires [3]. The first applications of this modeling approach to climate 
change were developed in a series of workshops in 2007-2009 [4-5]. 
Later applications focused on incorporating predator-prey interactions 
and disease dynamics; these applications analyzed the effectiveness of 
conservation measures for the world's most endangered cat, which is 
impacted by climate change [6], and for one of the most threatened 
North American mammals, which is impacted by plague [7]. These studies 
demonstrated that spatially structured prey-predator models allow 
realistic conservation planning that takes into account emerging 
threats such as climate change and infectious diseases.

One of the goals of these projects has been to contribute to the 
development of Red List Guidelines [8] for identifying species 
threatened by climate change. To test the effectiveness of the Red 
List criteria as an early-warning system for climate change-related 
extinctions, we adapted the coupled niche-population modeling approach 
to simulate generic life-history types instead of particular 
species.The resulting analysis found that climate change causes high, 
but predictable, extinction risks [9], and that the Red List system 
would provide several decades of warning time for species that might 
go extinct because of climate change [10]. In a related study, we 
combined the coupled niche-demographic models with recent advances in 
geochronological dating, palaeoclimate reconstructions and molecular 
techniques for retrospective modeling [11]. Our preliminary results 
suggest that such long-term retrospective analyses will improve 
efforts to predict the likely effects of future climate and other 
environmental change on biodiversity, and target conservation 
management resources most effectively.

*Research areas:* Species conservation; risk assessment; climate change*
*

*Methods keywords:* Coupled niche-demographic models; Matrix 
population models; Metapopulation models with dynamic spatial structure

*References*

[1] Akçakaya, H.R. and W.T. Root. 2013.RAMAS GIS: Linking Spatial Data 
with Population Viability Analysis.Version 6.0. Applied 
Biomathematics, Setauket, New York.

[2] Akçakaya, H.R., V.C. Radeloff, D.J. Mladenoff, and H.S. He. 2004. 
Integrating landscape and metapopulation modeling approaches: 
viability of the sharp-tailed grouse in a dynamic 
landscape.Conservation Biology 18:526-537

[3] Akçakaya, H.R., J. Franklin, A.D. Syphard, and J.R. 
Stephenson.2005. Viability of Bell's sage sparrow (/Amphispiza belli/ 
ssp. /belli/): altered fire regimes.Ecological Applications 15:521–531

[4] Keith, D.A, H.R. Akçakaya, W. Thuiller, G.F. Midgley, R.G. 
Pearson, S.J. Phillips, H.M. Regan, M.B. Araújo, T.G. Rebelo. 2008. 
Predicting extinction risks under climate change: coupling stochastic 
population models with dynamic bioclimatic habitat models. Biology 
Letters 4:560–563.

[5] Anderson, B., H.R. Akçakaya, M. Araújo, D. Fordham, E. 
Martinez-Meyer, W. Thuiller, B.W. Brook. 2009. Dynamics of range 
margins for metapopulations under climate change. Proceedings of the 
Royal Society B276:1415–1420.

[6] Fordham, D.A., H.R. Akçakaya, B.W. Brook, A. Rodríguez, P.C. 
Alves, E. Civantos, M. Triviño, M.J. Watts and M.B. Araújo. 2013. 
Adapted conservation measures are required to save the Iberian lynx in 
a changing climate. Nature Climate Change 3:899-903.

[7] Shoemaker, K.T., R.C. Lacy, M.L. Verant, B.W. Brook, T.M. Livieri, 
P.S. Miller, D.A. Fordham, and H.R. Akçakaya. 2014. Effects of prey 
metapopulation structure on the viability of black-footed ferrets in 
plague-impacted landscapes: a metamodelling approach.Journal of 
Applied Ecology 51:735–745.

[8] IUCN 2016. Guidelines for using the IUCN Red List categories and 
criteria. IUCN Standards and Petitions Working Group. 
http://www.iucnredlist.org/documents/RedListGuidelines.pdf.

[9] Pearson, R.G., J.C. Stanton, K.T. Shoemaker, M.E. Aiello-Lammens, 
P.J. Ersts, N. Horning, D.A. Fordham, C.J. Raxworthy, H.Y. Ryu, J. 
McNees, and H.R. Akçakaya. 2014. Life history and spatial traits 
predict extinction risk due to climate change. Nature Climate Change 
4:217-221.

[10] Stanton, J.C., K.T. Shoemaker, R.G. Pearson, H.R. Akçakaya. 2015. 
Warning times for species extinctions due to climate change. Global 
Change Biology 21:1066–1077.

[11] Fordham, D.A., H.R. Akçakaya, J. Alroy, F. Saltré, T.M. Wigley, 
B.W. Brook. 2016. Predicting and mitigating future biodiversity loss 
using long-term ecological proxies. Nature Climate Change 6:909-916.

-- 
H. Resit Akcakaya
Professor
Department of Ecology and Evolution
Stony Brook University
Stony Brook, New York 11794 USA
Tel: 1-631-632-8605
Fax: 1-631-632-7626
Resit.Akcakaya at stonybrook.edu
http://life.bio.sunysb.edu/ee/akcakayalab/

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