RBS Darwin Maule

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RBS Darwin Maule

• RBS Rapid Botanic Survey
• Current RBS work plan for Maule region
• What we expect to do with the data later
• Bioquality Genetic Heat Index of forests
• Stars categories of species

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RBS Rapid Botanic Survey

• Rapid 2 or more samples /day inform about all
  plants in a defined landscape unit. Plant species
  are harvested
• Botanic usually all vascular plants
• Survey samples across many patches of forest
  across a region or nation or study area

• Field methods analysis developed in Ghana,
  Cameroon, Ivory Coast, Sierra Leone, Malaysia,
  Honduras, Mexico, Trinidad Tobago

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RBS and other botanical samples

• Hybrid between normal herbarium collection
  strategy and forestry or vegetation plots
• RBS tailored to rapid data collection for
  prioritising biodiversity conservation
• Produces more complete data for each patch of
  forest than normal herbarium databases
• Similar to Braun-Blanquet and other surveys, but
  samples and methods less structured, unmeasured,
  for faster and different analyses
• Growth rates, timber volumes etc. not possible

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Aims of RBS

• Rapidly build a database of plant distribution
• Help prioritise forests for conservation
• Provide data for bio-quality analysis
• Objective score for environmental impact
  assessment. What is the value of the forest lost
  to this mine?
• To inform about species distribution and forest
  types
• To inform about plant ecology. Does this species
  occur mostly ion disturbed/ swampy habitats?
• Get people out into the field to increase their
  botanical wisdom and to collate botanical with
  other data e.g. photos, local opinions

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Rapid Botanic Survey basics

• 2-4 hand-picked sample areas day
• Simply record (collect) all plant species in a
  given landscape unit e.g. along forest stream
  A or along logging road b until new species
  records are exhausted.
• Count individual canopy trees (gt30 cm DBH or
  gt10cm in low forest)
• Ideally gt40 species AND gt40 trees before
  stopping, but more is no problem, and if fewer
  exist in the area, so be it.
• Photograph species for promotion of outputs

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RBS in Honduras, Mexico
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Darwin Trinidad RBS team
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RBS plans for Chile
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January 2007 team develops skills in Quile
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January 2007 RBS tried and discussed in various
vegetation types
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Plans for sampling Maule

• Where Maulinos coastal forests
• When Dry season, spring season
• Who Project team
• How Strategy ----
• extensive survey (region level, 75 points)
• intensive survey (local level, x points)
  e.g. 13 or 12 (depending
  on the landscape)

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What next? Data flow
Literature, WWW
RBS
Analyses Maps, Reports
Database
WWW Images, data
Herbarium Data
Consensus refinement Stars etc
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BRAHMS outline
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Ordination of RBS data

• RBS data can be put to many uses, e.g.
  vegetation ordinations and other user-designed
  indexes, like Pioneer Index or medicinal
  species in flora

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Bioquality

• Bio diversity is only about numbers of species in
  an area, as if all were equal
• Bioquality is about the concentration of valued
  species in an area, especially species only found
  in a few areas and so valued from a global
  conservation point of view
• The Genetic Heat Index is a standardised index of
  global bio-quality designed for use with RBS and
  other check-list data

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GHI Genetic Heat Index

• GHI is an index of bio-quality, showing degree of
  endemicity in a sample (any size) of species
• Endemic species on its own means little all
  species are endemic to somewhere
• Species restricted to smaller parts of the world
  contribute a higher score for GHI calculations

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Route to GHI via Stars
RBS samples in field (species list)
Put Species in categories Called Stars
Calculate weights for Stars
Calculate GHI 100 x (No. Species in each star x
weight) /Number of spp.
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Stars

• All Species put into categories called Stars
• For practical reasons, based on available data in
  herbaria, flora, monographs
• E.g. Black Star species very restricted range
  and of high conservation concern
• Green Star species of no conservation concern,
  with wide range
• Gold and Blue intermediate.
• Green star species which are widespread but
  mostly threatened by heavy exploitation can be
  defined as Red Stars

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Summary of Stars
Black Most rare or taxonomically extreme
Gold
Blue
Green Common and widespread not unusual
SCARLET As Green, but highly overexploited
RED As Green, but heavily exploited
PINK As Green, but some exploitation
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Defining Star of each species
Global range, Chile range, ecology, Local
abundance, taxonomy
Refine Criteria for Stars

• Mean degree (or 100km) square ranges of Stars in
  various countries should be similar
• Stars define global rarity and conservation
  priority, so base mostly on biogeography but with
  some attention to taxonomy ecology.
• Agreement and review with other botanists useful
• Criteria must be practical to implement

Find average no. of degree squares For subset
of species of each Star
Weights for each Star
Assign Stars to species
Implement In rules guidelines
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Species distribution maps
Distribution maps of herbarium collections of
various African species of limited distribution
Known distribution of typical widespread (Green
Star) species of African forest (c. 100 degree
squares)
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Calculation of weights

• Example from Honduras /Mexico
• Weights may differ in different countries due to
  need to keep criteria simple
• No. degree squares calculated for a subset of
  species of each square, depending on available
  maps and recent monographs

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e.g. Star Criteria for Chile?
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(Chile Argentina)
(Chile Argentina)
?
Open areas from Ecuador to Argentina
Argentina, New Z
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Calculation of GHI
The Weight in B. for each Star is in inverse
proportion to the number of degree squares
occupied on average by the species of that Star
relative to Green. Green Star weights are then
set to zero.
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Bioquality map

• GHI scores interpolated (krigging in Surfer) to
  indicate local hotspots in Ghana

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Variation of GHI in Ghana
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Photo libraries and web presence

• Database of plant distribution and photographs
  for future use
• Presence of Talca bioquality on web opens
  opportunities and adds publicity

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Thanks

• William Hawthorne says many thanks to the
  Darwin-Maule team for a great stay in Chile,
  enthusiastic and interesting field work (and
  pretending to understand my sign language)
• José San Martin, Patricio Peñailillo, Rolando
  Garcia, Persy Gomez (UTAL)
• Cesar Sepúlveda Pedro Garrido (Codeff) Franz
  Arnold (consultant) Carolinas Rojas (Celco)