Ancestral_niche_reconstruction

Transcript

1. -­‐   1 Requirements Phylogeny Best  choice:  a  sample  of  dated  molecular   phylogenies.     Ref:  Roquet,  C.,  Thuiller,W.,and  Lavergne,S.  (2012).  Building   megaphylogenies  for  macroecology:  taking  up  the  challenge.   Ecography,  36(1):013-­‐026.   Niche Niches  are  inferred  by  combining     a)  species  distribuLon  maps  with     b)  climaLc  layers  (temperature,  precipitaLon,  etc).     Predicted   absence   Predicted   presence   a)  Species  distribuLon   b)  ClimaLc  layers   Raw  data  representaLon     of  the  niche   Niche  model   Mean  value   EnLre  area   Occupied  area   Number     of  sites   Niche  sta*s*cs     • Mean,  min,  max   • EnLre  distribuLon   • …     Note:  the  parameters  finally   obtained  from  different   approaches  may  differ     (mean  value  in  this  example).   +   Occurrence   probability   5      6      7      8    9    10    11    12    13  °C   5      6      7      8    9    10    11    12    13    °C   Chronogram •  Niche  models  are  preferable  to  raw  data  representaLons   •  The  mean  value  is  not  always  the  opLmal  staLsLc;   reconstrucLng  the  whole  distribuLon  is  more  desirable   2 Choosing the best model Time CONSTANT RATE OF EVOLUTION Brownian motion (BM) Orstein-Uhlenbeck with single optimum (OU) OU with n selective optima (OUn ) TIME-DEPENDENT RATE OF EVOLUTION Niche filling models Early burst (EB) decelerating rates ACDC BM + accelerating/decelerating Pagel’s δ accelerating/decelerating • Random drift • Random punctuated change • Stabilizing selection/ stasis • Stabilizing selection with clade-specific optima • Character displacement/ Adaptive radiation/ Divergence • Decelerating evolution EVOLUTIONARY PROCESSES EVOLUTIONARY MODELS I. Identifying plausible evolutionary processes BM OUn EB    BM            OUn              EB   LogL  -­‐36              -­‐30              -­‐32   AIC  -­‐35              -­‐38              -­‐37   BIC  -­‐37              -­‐42              -­‐40     3 Reconstructing the past Model-­‐free1      Model-­‐based  methods   WSqCP/PIC                            =            ML/GLS  +  BM          ≅        Bayesian  +  BM   WSqCP  +  OU  tree      =            ML/GLS  +  OU            ≅        Bayesian  +  OU   II. Model fitting III. Model evaluation Ancestral niche reconstruction – time machine user manual Lara Budic and Carsten F. Dormann, Department of Biometry and Environmental System Analysis, University of Freiburg, Germany, lara.budic@biom.uni-freiburg.de 1Model-free methods (independent contrasts and weighted squared-change parsimony) implicitly assume Brownian motion model of evolution. When inferring ancestral values that evolved under other models, the tree is rescaled accordingly. http://upload.wikimedia.org/wikipedia/commons/6/63/Cacao_spe... http://upload.wikimedia.org/wikipedia/commons/6/63/Caca Current range Ancestral range Present-day map Paleoclimatic map Fossil records Paleoclimatic map http://upload.wikimedia.org/wikipedia/commons/6/63/Cacao_spe... •  Check whether reconstructed climate values match with paleoclimate data. •  Ancestral species range should be projected to paleoclimatic maps. •  When available, fossil records can prove species presence in the study area and/or in the predicted ancestral range. 4 Validation 2 1 4 4 9 5 6 8 3 5 4 7 6 4 5 3 2 2 7 7 6 5 5 6 6 5.5 6 5 Reconstructiong ancestral temperature values Present day values Ancestral values Budic, L. and Dormann, C.F. (2013) The challenging task of reconstructing the ancestral climate niche: a review of approaches and steps towards a best practice (submitted) Pagel,  M.  et  al.  (1999).  Inferring  the  historical  pacerns  of  biological  evoluLon.  Nature,  401(6756):877–884.   Evans,  M.,  Smith,  S.,  Flynn,  R.,  and  Donoghue,  M.  (2009).  Climate,  niche  evoluLon,  and  diversificaLon  of  the  ”bird-­‐cage”  evening  primroses  (Oenothera,  SecLons  Anogra  and  Kleinia).  The  American  Naturalist,  173(2):225–240     (If  possible…)   Temperature   Temperature