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An ( short ) Introduction to Species-Abundance Distribution Curve

BarEcore – Data Analysis Workshop. An ( short ) Introduction to Species-Abundance Distribution Curve. G. Certain – from Fisher et al. 1943, Preston 1948, Mc Arthur 1960, Hubbel 1979, Sugihara 1980, Hubbel 1997, McGill et al. 2007, O’Dwyer et al. 2009, Szilic et al. 2009.

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An ( short ) Introduction to Species-Abundance Distribution Curve

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  1. BarEcore – Data Analysis Workshop An (short) Introduction to Species-AbundanceDistributionCurve G. Certain – from Fisher et al. 1943, Preston 1948, Mc Arthur 1960, Hubbel 1979, Sugihara 1980, Hubbel 1997, McGillet al. 2007, O’Dwyer et al. 2009, Szilic et al. 2009

  2. What is a SAD ? It’s a way to describetherelative abundanceofspecieswithin a sampleof a community Rare species Numberofspecies Distribution Abundant species Abundances 1 2 3 4 6 8 9

  3. Therearevariouswaysof plotting the SAD: Abundance, log(abundance), proportions Abundance, log(abundance), ranks Thesevariouswaysof plotting SAD potentially show highvariability, butthehollowcurve is a constantacross most ofecological systems

  4. SADs Vs othertools to studycommunity:

  5. SAD – a briefhistory (from Hubble, chap 2) The fist studies were inductives, i.e. observation -> research for a statistical model: A 620 speciescollectionsampled by Corbet in Malaya α = Result in a negative binomial distribution, withconstraints Assumption: The ”true” relative abundanceofspecies is described by a gamma function sampled by a Poissonprocess (unselective trapping) 0- truncated Gamma Poisson Negative Binomial x The Fisher logseries = The total numberofspecies in thefieldis assumedinfinite

  6. Emergenceofdeductiveapproaches: “Earlier investigations, discussed elsewhere, fit known statistical curves of uncertain biological meaning to the data. A more fruitful approach seems to be to predict curves on the basis of simple biological hypotheses and to compare these with the data.” Example: The ”broken stick” hypothesis The resourceshared by a communitycan be represented by a stick A communityof S species broke thestick in S-1 random locations The followingsegment-lengthdistributionproducereasonablehollowcurves for closelyrelatedcommunity(i.e. communitysharing a commonresource)

  7. The log-normaldistribution: a matter ofsamplesize In 1948, Preston criticizedthelogseriesoffisherbecause it wouldsystematicallypredictthatthe singleton class is the most numerous, and argued it was an artifact due to samplesize. Therefore, he introducedtheuseofthe log normal distribution. Low sampling effort High sampling effort In 1980, Sugiharanotedthat breaking thesticksequentiallyproduced a log-normaldistribution S N But in recentyears, furtherincrease in samplesizeshowedthatthenumberof rare specieswas still underestimated by thelognormal…

  8. Hubbel’sneutraltheory • Birth (b), death (d) and speciation (ν)aredensity independent , stochasticprocesses. • b<d, so thateveryspeciesgoestowardextinction • ν compensate for extinction. (Hubbell1979) (and nothingelse matters….) θ = 2*Jm*ν Jm=metacommunitysize Ecological drift (randomdeath, birth and speciation) is theonlyprocess driving thecommunitydynamic.

  9. Recentdevelopmentsonneutraltheory: sizematters. (PNAS 2009) O’Dwyer and colleaguesproduced a neutralmodelwherethedemographic rates ofindividualsdirectlydependsontheirsize Eachindividual undergoes a continuous, deterministic growth process with size-dependent growth rate, g(m). Birth, death, and speciation processes are stochastic. Death rate d(m) is size dependent, while birth rate b and speciation rates νare independent. The modelintroduce a newcriterion for communitydiagnostic: species – biomassdistribution

  10. And space, and scale matters… (PNAS 2009) Howspatial correlation and turn-over rate in SADsaffectSAD ? AnySAD is a compositeofSADs 0 spatial correlation 1 White: lowturn-over Black: highturn-over

  11. So whataretheexpectations for the present workshop ? - producevariousdiagnostic plots (SAD, SBD, Rank abundance plots etc…) withthebarentssea data - fitSADswithwellknownmethods (Fisher logseries, log normal distribution, Hubbel’sneutraltheory, Poisson log normal distribution) - Explorebasicpatternsin SAD/SBD parameters in space and time

  12. Data extracted from årsmaterial Number, Biomass, Size (median – quantile) Sampling info (gear, time, depth, date, vessel, serialno, etc…) ~ 700 Taxa Trawl #1 Trawl #2 1980 - 2010 Trawl #3 …

  13. Later on, a large numberof alternative statisticalmodels have beenproposed as substitute…

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