Project Funding: 2009 - 2014

NRA: 2008 NASA: Biodiversity   

Funded by NASA

Abstract:
Climate change is rarely considered when implementing conservation measures to address species-level threats. In particular, the International Union for Conservation of Nature (IUCN) Red List, which is widely used to guide conservation policy and spending, does not explicitly incorporate climate change into its criteria to evaluate extinction risk. We aim to address this shortcoming by developing a modeling framework that links remote sensing of the environment with in situ biological data sets and global climate model predictions. We will couple habitat suitability models (including the Maximum Entropy method, Maxent) with metapopulation simulations (implemented in RAMAS software). These models will link remote sensing products (e.g., land cover classifications, NDVI, EVI, LAI, GPP, NPP, fPAR) with biodiversity data from natural history collections and biodiversity surveys, and future climate scenarios generated for the Intergovernmental Panel on Climate Change (IPCC). Our linked modeling approach will enable extinction risks under climate change to be assessed based on both landscape and demographic properties, therefore providing more reliable assessments, subject to fewer uncertainties, than when applying habitat suitability models alone. The principal objectives of the proposed project are to: 1) test the use of remote sensing products alongside in situ biological data and climate data for building habitat suitability models; 2) link habitat suitability models and metapopulation simulations to assess extinction risk under climate change; 3) investigate the impact that including versus excluding remotely sensed data has on assessments of extinction risk; 4) develop guidelines to ensure that remote sensing products are fully integrated into ongoing efforts to incorporate climate change within the IUCN Red List criteria. We will test our approach using the herpetofaunas of the United States (where in situ datasets are relatively abundant) and Madagascar (where data is much more limited) as case studies. Through collaboration with the IUCN, we will produce guidelines and software tools to advance the use of remote sensing products in environmental forecasting that influences policy and resource management. Our project will therefore expand and accelerate the realization of societal benefits from Earth system science.

Publications:

Aiello-Lammens, M. E., Akcakaya, H. R. 2016. Using global sensitivity analysis of demographic models for ecological impact assessment. Conservation Biology. 31(1), 116-125. DOI: 10.1111/cobi.12726

Akaya, S. E., Kivanc, M. 2008. Isolation and identification of thermophilic bacteria species from hot springs. Journal of Biotechnology. 136, S608. DOI: 10.1016/j.jbiotec.2008.07.1408

Berton C. Harris, J., Fordham, D. A., Mooney, P. A., Pedler, L. P., Araujo, M. B., Paton, D. C., Stead, M. G., Watts, M. J., Resit Akcakaya, H., Brook, B. W. 2012. Managing the long-term persistence of a rare cockatoo under climate change. Journal of Applied Ecology. 49(4), 785-794. DOI: 10.1111/j.1365-2664.2012.02163.x

Cullen, L., Stanton, J. C., Lima, F., Uezu, A., Perilli, M. L. L., Akcakaya, H. R. 2016. Implications of Fine-Grained Habitat Fragmentation and Road Mortality for Jaguar Conservation in the Atlantic Forest, Brazil. PLOS ONE. 11(12), e0167372. DOI: 10.1371/journal.pone.0167372

Fordham, D. A., Akcakaya, H. R., Araujo, M. B., Keith, D. A., Brook, B. W. 2013. Tools for integrating range change, extinction risk and climate change information into conservation management. Ecography. 36(9), 956-964. DOI: 10.1111/j.1600-0587.2013.00147.x

Fordham, D. A., Akcakaya, H. R., Brook, B. W., Rodriguez, A., Alves, P. C., Civantos, E., Trivino, M., Watts, M. J., Araujo, M. B. 2013. Adapted conservation measures are required to save the Iberian lynx in a changing climate. Nature Climate Change. 3(10), 899-903. DOI: 10.1038/nclimate1954

Fordham, D. A., Resit Akcakaya, H., Araujo, M. B., Elith, J., Keith, D. A., Pearson, R., Auld, T. D., Mellin, C., Morgan, J. W., Regan, T. J., Tozer, M., Watts, M. J., White, M., Wintle, B. A., Yates, C., Brook, B. W. 2012. Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming? Global Change Biology. 18(4), 1357-1371. DOI: 10.1111/j.1365-2486.2011.02614.x

Pearson, R. G., Stanton, J. C., Shoemaker, K. T., Aiello-Lammens, M. E., Ersts, P. J., Horning, N., Fordham, D. A., Raxworthy, C. J., Ryu, H. Y., McNees, J., Akcakaya, H. R. 2014. Life history and spatial traits predict extinction risk due to climate change. Nature Climate Change. 4(3), 217-221. DOI: 10.1038/nclimate2113

Stanton, J. C., Pearson, R. G., Horning, N., Ersts, P., Resit Akcakaya, H. 2011. Combining static and dynamic variables in species distribution models under climate change. Methods in Ecology and Evolution. 3(2), 349-357. DOI: 10.1111/j.2041-210x.2011.00157.x

Stanton, J. C., Shoemaker, K. T., Pearson, R. G., Akcakaya, H. R. 2014. Warning times for species extinctions due to climate change. Global Change Biology. 21(3), 1066-1077. DOI: 10.1111/gcb.12721

Stanton, M. L. 1987. A Balanced View of Populations. Ecology. 68(2), 452-452. DOI: 10.2307/1939279

2011 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• Modeling Species Distributions to Support Assessment of Extinction Risks under Climate Change   --   (H. Resit Akcakaya, Richard Pearson, Jessica C. Stanton, Ned Horning, Peter Ersts)   [abstract]   [poster]

More details may be found in the following project profile(s):

• NASA Biological Diversity & Ecological Conservation (BDEC) Project Profile