NAT.B05 Ecosystem Conversion
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.
Formula
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)
