Readings

Species-fragmented area relationship

  • Reading for QAECO reading group
  • relationship between increasing number of species and increasing area of habitat
    • (so I suppose inverse is true, e.g. climate change reduce area of habitat, reduce number of species?)
    • predict number of extinctions due to loss of habitat
  • the issue is fragmentation
    • habitat loss generally results in a fragmented (sub) habitat
    • SAR assumes contiguous regions (think a circle getting smaller)
    • fragmentation is when holes appear (think a doughnut)
  • (meta) population capacity is essentially the carrying capacity of the habitat
  • fragmentation causes this to decline
    • e.g. due to disconnect between fragments
  • SFAR (species-fragmented area relationship) fits better than SAR in simulations
  • Figure 1
    • the authors suggest the SAR does not fit the number of species well, but it looks like it does to me? The lines are pretty close to the points?
    • I think perhaps the figure legend is not described well — the lines are not SARs but just general fitted lines?
  • Species traits
    • when including the fragmentation part, the authors suggest a large amount of variation in the ratio of extinction and colonisation
    • this has an effect on their $b$ parameter
    • how are the models fit? stupid pnas, need to check in supplementary material
  • Case study uses only 14 points
  • they suggest that species number is reduced due to fragmentation
  • a better visualisation would be to use points proportional to $\lambda$ in Figure 4A
  • They suggest hat SFAR is better than SAR, due to a difference in AICc of 2.44 (!)
  • furthermore, the least-squares value of the area coefficient is negative, meaning that conditional on $\lambda$, the number of species $S$ is increasing as area $A$ decreases
    • what!?
    • this same thing happens in eqn 3, where if $z < 0$, if $A_{\text{new}} < A$, \$S~new~/S >1 \$!
  • they do discuss what they term hidden parameters: those used for estimating $\lambda$
    • perhaps these should be estimated in a hierarchical model?