26/10, 2021

Methods

  • Using prioritizr for optimization
  • two approaches
    • Minimum cost to approach goals
    • Maximum gain given a certain budget (better to get to target areas)
  • 987 species as target features

Biodiversity

Data for Denmark

  • From BIEN, we looked for all the presences of species present in Denmark
    • Native: 987
    • Invasive: 208 (more introduced species have also been modeled)
  • Model current and 4 future scenarios

Concensus (Example)

  • When current and future ranges are aligned

Concensus richness

  • Present richness vs concensus richness
  • Better options with migrations, artscore, and other metrics
  • Other taxa

Human dimension

Agriculture

  • Naidoo and Iwamura (2007)
  • Based on potential crop and livestock production
  • Does not consider climate change (We can do better)

Human footprint

  • Copenhagen shows how different they are

Prioritization

Naive prioritization

  • Only take into account species (10% coverage)

Add Agriculture

  • Add Agriculture as cost (min cost)

We dont start from scratch

  • Start with protected areas, eliminate cities (HFP)

Using weights and different budgets

closest to 10 and 30%

Other things to add

Prioritization doesn’t have to be about species

  • Add ecosystem services as features to be preserved
  • Add other needs as cosntrains (Carbon stock among others)