1.2. MINERAL SYSTEMS-BASED PROSPECTIVITY APPROACH The relative importance and expression of mineral system elements vary according to deposit type. In porphyry–skarn systems, key permissive factors include magmatic age and composition, lithological associations, structural configuration, and tectonic setting. These elements must converge spatially and temporally to generate an economically significant system. This study applies a process-based prospectivity framework structured around system components, geological processes, and scale dependency, following the approach outlined by McCuaig et al. (2010) and subsequent adaptations for regional targeting. Critical processes (causes) are translated into spatially mappable target elements (consequences), which are then represented by predictor maps derived from geological and structural datasets. Each predictor is weighted conceptually according to its relevance at the working scale. Elements deemed essential at regional scale are prioritized, whereas lower-order controls that operate at deposit scale are excluded to avoid overfitting and conceptual inconsistency. Therefore, the same prospective approach by Mineral Systems (System, processes and scales) of Marchena et al (2025) based on McCuaig et al. (2010) has been used. (Figure 2.) Figure 2 - Mineral Systems analysis framework, showing the critical processes (causes), target elements (consequences), and the representation criteria of the target elements (predictor maps or datasets). Where: reddish cream indicates Importance 1; yellow–orange indicates Importance 2; and green indicates Importance 3 (not required to be included at the corresponding working scale). 2. PROSPECTIVITY MAP OF THE METALLOGENIC PROVINCE OF THE ANDAHUAYLAS-YAURI BATHOLITH 2.1. DATASETS AND SPATIAL PROXIES Regional-scale modeling was conducted using publicly available datasets, primarily sourced from the GEOCATMIN platform of the Geological Survey of Peru (INGEMMET). Only datasets consistent with the working scale (provincial–regional) were incorporated to avoid conceptual and spatial mismatch. Datasets were selected and translated into spatial proxies according to their relevance within the Mineral Systems framework. The complete dataset inventory and their assigned mineral system processes are summarized in Table 1.
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