Large-scale and small-scale metal mining operations may not have been considered in the past as big threats to the observed local to global biodiversity pressure, but their zones of influences may adversely change species habitats, directly, indirectly, at local and regional scales. In this study, the intensity index on biodiversity is generated from mining gold and copper in Itogon and Tuba areas in the Philippines. These two areas are located in the Northern Luzon with high base metal concentration in porphyry veins deposits with a host of biodiversity due to the distinct biogeographic, altitudinal gradient and climate. The endemic and threatened flora Nepenthes Bellii K. Kondo, Shorea polysperma, Pterocarpus indicus Willd and Lilium philippinense Baker within three mining sites indicated as X, Y, Z are used as species under threat and with multiple variable summation of their geospatial pattern of occurrences and by using by Python Programing Language to compute the Mining Factors (MF) from the Mines Annual Production and Percentage Grades, thereafter, the MF is multiply by the Biodiversity Factor (BDF) which is define as the product of the mines Area Factors (AF) and Protected Area Factor, and the values obtained are divided by Fibonacci Extinction Factor; which is the species Area of Occupancy(AOO) divided by the Extent of Occurrence(EOO) raised to the power of the corresponding Fibonacci Number. The final output is multiplied by the Potential Ecological Risk Indexes from the Heavy metals released from the mines. FEF is generated from QGIS geospatial analysis and the IUCN biodiversity Red List Category that finally yields the MintBio index. MintBio index values generated are subjected to linear regression analysis using Microsoft Excel data analysis tool to test the statistical significance. The MintBio indexes obtained are independent of mining scales or MF but depend heavily on the FEF and AF suggesting that MintBio as a model could serve as an attribution and intensity index to quantifying mining pressure on the ecosystem and species diversity that are often ignore using only biodiversity proxies such as trees cover and protected area. The value of the MintBio obtained in this study ranges from 686.756 of mine Z to 33,614,780.60 of mine Y indicating vast differences that were captured due to the higher threat of mine Y to the endemic and threatened species within 5km from the mine center. The inclusion of conservation factors to the index would further increase such sensitivity for a better evaluation and such would create the opportunity for incentives for mines operating responsibly and with high conservation tract records. MintBio is a potential model to improve policy targets in biodiversity monitoring, impact verification, corporate and environmental management in eco-designs, eco-labelling for huge metal consumption industries and would foster validation of sustainability claims regarding mining if integrated into blockchain as solution framework for proof-of-zero impact to biodiversity supply chain and international financing standardization for metals trade impact index options from mines in the Philippines and those across the globe.

Keywords: Biodiversity, mining pressure, Geospatial Analysis, Mining Intensity Index, Policy target, Blockchain