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As the global climate continues to warm, changes in local climate conditions put populations of many species at risk of severe decline and even extinction. Predicting which species are most vulnerable to changing conditions is challenging, because climate interacts different life stages in complex ways. Population models allow natural resource managers to integrate the effects of climate across life stages and provide a powerful tool to inform management decisions. However, care must be taken to match model structure to a species’ biology and recognize the limitations of the data used to parameterize models when interpreting predictions.

Related Article(s):


Contributor(s): Dr. Brian Hudgens


Key Resource(s):

  • Quantitative Conservation Biology[1]
  • Evaluating the Use of Spatially Explicit Population Models to Predict Conservation Reliant Species in Nonanalogue Future Environments on DoD Lands, Strategic Environmental Research and Development Program (SERDP)[2].

Climate Change and No-analogue Environmental Conditions

The global climate has been changing throughout the past century, with continued changes predicted over coming decades. Generally, temperatures are getting warmer throughout U.S. and worldwide (IPCC 2014). Precipitation patterns are also changing, with some regions of the U.S.  getting drier, others getting wetter (Abatzoglou 2013, IPCC 2014).  Further changes are occurring in the timing and duration of precipitation events, with extreme weather events becoming more common (Abatzoglou 2013, IPCC 2014).

  1. ^ Morris, W.F., and Doak, D.F., 2002. Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis. Sinauer Associates, Inc. Publishers, Sunderland, Massachusetts, USA. ISBN: 978-087893546-8
  2. ^ Hudgens, B., Abbott, J., Haddad, N., Kiekebusch E., Louthan A., Morris W., Stenzel L., Walters J., 2020. Evaluating the Use of Spatially Explicit Population Models to Predict Conservation Reliant Species in Nonanalogue Future Environments on DoD Lands. Strategic Environmental Research and Development Program (SERDP), Project RC-2512 Final Report pdf