Partial Order and Rank Range Runs for Compositional Complexes in Landscape Ecology and Image Analysis, with Applications to Restoration, Remediation, and Enhancement

Present purpose is to provide convenient computational capability and visualizations for progressive/partial prioritization based largely in concepts of partial ordering and implemented in R as illustrated in a context of conservation and sustainable stewardship across landscapes with ecosystem services as a complex multidimensional domain that must be placed in public and private perspective in pursuit of multi-resource management. Practical perspective is promoted by graphic visualization and weak orderings with local partial order modeling (LPOM) methods for screening of settings and scenarios involving interactions of ecosystem elements as evidenced by environmental indicators. Current contributions include distal data relative to remediation and retention, crucial corners in perspective plots, ascribed advantage as an outcome of a rating regime with trapezoidal tracking and ORDIT triangular orderings, complementary cases, median mismatches relative to interaction of indicators, and interleaving indicators to condense criteria. A suggested strategy to circumvent computational constraints is partitioning the pool into collectives by clustering, pursuing precedence of partitions, and then prioritizing in particular partitions. When prime prospects have been obtained, detailed determinations can be done with partial ordering procedures involving Hasse diagrams and similarly complex constructs that are difficult to apply with many cases and/or indicator criteria.