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NAT.B05 Ecosystem Conversion
What did the company score for NAT.B05 Ecosystem Conversion in the Nature Benchmark?
18824611
Formula

About the data

Land use change through the conversion of natural habitats is among the most significant drivers of biodiversity loss in terrestrial ecosystems. Agricultural production alone is responsible for 80% (WWF, 2020) of global deforestation. Moreover, extractive sectors including the metals and mining and oil and gas sectors have significant impact on converting ecosystems through their business activities, including land degradation or conversion of wetlands. Aligning with the SBTN interim targets to ensure zero deforestation and conversion from 2020 in all corporate supply chains, this indicator focuses on ensuring companies set targets to minimize their footprint across all relevant ecosystem realms.

A note on the scoring system

Wikirate uses a standardized 10-point scoring system to enable comparison of company scores across different benchmarks. In the Nature Benchmark, companies can earn 1 point per indicator, which are then added together and calculated as a percentage of the total score for a measurement area (MA) to determine the final score for the MA. The overall Wikirate score is calculated by combining these scores with the appropriate weightings, and converting them to a 10-point scale. For instance, if a company achieves a final score of 50, the corresponding Rating will be 5.

score = (x) -> 
  if x == "Yes"
    10
  else
    0
    
redistributed_weights = (weights, values) ->
  num_of_weighted_values = weights.length  
  for value, index in values
    if value == "Not Applicable"
      num_of_weighted_values -= 1
      redistributed_weight_value = weights[index]
      for weight, i in weights
        if weight == 0
          continue
        weights[i] = weight + redistributed_weight_value/num_of_weighted_values
      weights[index] = 0
  weights
  
weights = [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]
ecosystem_conversion = [commitment, evidence, time_bound_targets, high_risk_commodities, sourcing_disclosure, coversion_free_supply_chain, minimization_commitment, minimization_evidence, minimization_system_disclosure, minimization_targets_disclosure]
redistributed_weights(weights, ecosystem_conversion)

weights.reduce((weighted_sum, weight, index) -> 
              weighted_sum + weight*score(ecosystem_conversion[index])
             , 0)
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World Benchmarking Alliance
commitment
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World Benchmarking Alliance
evidence
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World Benchmarking Alliance
time_bound_targets
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World Benchmarking Alliance
high_risk_commodities
sourcing_disclosure
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World Benchmarking Alliance
coversion_free_supply_chain
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World Benchmarking Alliance
minimization_commitment
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World Benchmarking Alliance
minimization_evidence
minimization_system_disclosure
minimization_targets_disclosure
Topics
Value Type
Number
Options
Researchable
no
Research Policy
Community Assessed