Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth

Abstract

Background: Identifying a subset of taxa that maximizes phylogenetic diversity is a cornerstone of quantitative conservation planning. Traditionally, phylogenetic diversity is defined over a phylogenetic tree in which leaves resemble present-day taxa and the branch lengths capture the estimated evolutionary distinctiveness. While maximizing phylogenetic diversity is computationally tractable on trees with unit costs, the problem becomes computationally intractable when transitioning to phylogenetic networks or to budgeted versions in which protecting taxa incurs non-homogeneous costs. This paper addresses these two challenges together, providing definitions and a comprehensive analysis of three distinct variants of budgeted phylogenetic diversity on networks.Results: We conduct our study through the lens of a small structural parameter, node scanwidth ($nsw$), which measures the tree-likeness of a phylogenetic network. Given a tree-extension of width $nsw$, we show that two of the considered variants can be optimized in $\mathcal{O}^*(3^{nsw} \cdot B^2)$ time, where $B$ is the budget. For the computationally harder third variant, we provide an algorithm to compute phylogenetic diversity scores in $\mathcal{O}^*(4^{nsw})$ time. We further contribute the first exact algorithms to compute node scanwidth itself. On highly reticulated, simulated networks with several hundred taxa and heterogeneous costs, our implementation computes phylogenetic diversity scores and optimal node scanwidth in fractions of a second, and the budgeted optimization algorithms significantly outperform existing benchmarks previously limited to unit-cost scenarios. Conclusions: Node scanwidth proves to be a small and computable parameter that makes budgeted phylogenetic diversity tractable on realistic networks, scaling comfortably to a thousand taxa. This narrows the gap between reali...