TY - JOUR
T1 - The ice age ecologist
T2 - Testing methods for reserve prioritization during the last global warming
AU - Williams, John W.
AU - Kharouba, Heather M.
AU - Veloz, Sam
AU - Vellend, Mark
AU - Mclachlan, Jason
AU - Liu, Zhengyu
AU - Otto-Bliesner, Bette
AU - He, Feng
PY - 2013/3
Y1 - 2013/3
N2 - Aim We play the role of an ice age ecologist (IAE) charged with conserving biodiversity during the climate changes accompanying the last deglaciation. We develop reserve-selection strategies for the IAE and check them against rankings based on modern data. Location Northern and eastern North America. Methods Three reserve-selection strategies are developed. (1) Abiotic: the IAE uses no information about species-climate relationships, instead maximizing the climatic and geographic dispersion of reserves. (2) Species distribution models (SDMs): the IAE uses boosted-regression trees calibrated against pollen data and CCSM3 palaeoclimatic simulations from 21 to 15 ka bp to predict modern taxon distributions, then uses these as input to the Zonation reserve-ranking program. (3) Rank-and-regress: regression models are used to identify climatic predictors of zonation rankings. All strategies are assessed against a Zonation ranking based on modern pollen distributions. Analysis units are ecoregions and grid cells. Results The abiotic strategy has a negative or no correlation between predicted and actual rankings. The SDM-based strategy fares better, with a significantly positive area-corrected correlation (r= 0.474, P < 0.001) between predicted and actual rankings. Predictive ability drops when grid cells are the analysis unit (r= 0.217, P = 0.058). Predictive ability for the rank-and-regress strategy is similar to the SDM results. Main conclusions For the IAE, SDMs improve the predictive ability of reserve-selection strategies. However, predictive ability is limited overall, probably due to shifted realized niches during past no-analogue climates, new species interactions as species responded individually to climate change, and other environmental changes not included in the model. Twenty-first-century conservation planning also faces these challenges, and is further complicated by other anthropogenic impacts. The IAE's limited success does not preclude the use of climate scenarios and niche-based SDMs when developing adaptation strategies, but suggests that such tools offer at best only a rough guide to identifying possible areas of future conservation value.
AB - Aim We play the role of an ice age ecologist (IAE) charged with conserving biodiversity during the climate changes accompanying the last deglaciation. We develop reserve-selection strategies for the IAE and check them against rankings based on modern data. Location Northern and eastern North America. Methods Three reserve-selection strategies are developed. (1) Abiotic: the IAE uses no information about species-climate relationships, instead maximizing the climatic and geographic dispersion of reserves. (2) Species distribution models (SDMs): the IAE uses boosted-regression trees calibrated against pollen data and CCSM3 palaeoclimatic simulations from 21 to 15 ka bp to predict modern taxon distributions, then uses these as input to the Zonation reserve-ranking program. (3) Rank-and-regress: regression models are used to identify climatic predictors of zonation rankings. All strategies are assessed against a Zonation ranking based on modern pollen distributions. Analysis units are ecoregions and grid cells. Results The abiotic strategy has a negative or no correlation between predicted and actual rankings. The SDM-based strategy fares better, with a significantly positive area-corrected correlation (r= 0.474, P < 0.001) between predicted and actual rankings. Predictive ability drops when grid cells are the analysis unit (r= 0.217, P = 0.058). Predictive ability for the rank-and-regress strategy is similar to the SDM results. Main conclusions For the IAE, SDMs improve the predictive ability of reserve-selection strategies. However, predictive ability is limited overall, probably due to shifted realized niches during past no-analogue climates, new species interactions as species responded individually to climate change, and other environmental changes not included in the model. Twenty-first-century conservation planning also faces these challenges, and is further complicated by other anthropogenic impacts. The IAE's limited success does not preclude the use of climate scenarios and niche-based SDMs when developing adaptation strategies, but suggests that such tools offer at best only a rough guide to identifying possible areas of future conservation value.
KW - Climate change
KW - Niche models
KW - No-analogue climates
KW - Palaeoecology
KW - Pollen
KW - Reserve selection
KW - Species distribution models
KW - Zonation
UR - https://www.scopus.com/pages/publications/84873955627
U2 - 10.1111/j.1466-8238.2012.00760.x
DO - 10.1111/j.1466-8238.2012.00760.x
M3 - Article
AN - SCOPUS:84873955627
SN - 1466-822X
VL - 22
SP - 289
EP - 301
JO - Global Ecology and Biogeography
JF - Global Ecology and Biogeography
IS - 3
ER -