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Abstract
Anthropogenic impacts like climate change, pollution, and habitat loss represent ominous environmental threats that can seem insurmountable to concerned citizens. Habitat loss through urbanization presents a particularly acute threat to insect pollinators, which are essential to human agricultural systems and human well-being. Herein, we introduce a user-friendly online modeling tool, The Urban Pollinator Matrix, that predicts how actions initiated by citizens and municipalities can benefit pollinators in backyards and across local communities. The Urban Pollinator Matrix applies a fuzzy interaction web approach to qualitatively model how backyard and community-scale actions can increase pollinator populations. We demonstrate an application of this tool by contrasting how cultivating native flowering plants vs. discontinuing traditional lawn care (i.e., lawn mowing and broadleaf herbicide use) in Missoula, MT, USA, might affect urban pollinators. Our model predicts that reducing traditional lawn care by 50% would increase pollinators modestly, with generalists like honeybees (Apis mellifera) benefiting most. In contrast, increasing native landscaping to levels comparable with ornamental landscaping (60% of the community), with no constraints on lawn care, was predicted to generate substantial increases in pollinator abundance, particularly for sensitive groups like bumblebees (Bombus spp.) and other native bees. These predictions suggest that cultivating native plants can achieve far greater benefits for important pollinator groups than less socially acceptable actions like discontinuation of traditional lawn care. The Urban Pollinator Matrix provides a modeling template for citizens and municipalities around the globe to incorporate pollinator conservation into urban planning for the betterment of the planet.
Citation
Pearson, Dean E.; DePuy, Alli L. W.; Kuhlman, Marirose P. 2025. Inspiring citizens and municipalities to initiate pollinator conservation: The urban pollinator matrix modeling tool. Urban Ecosystems. 28: 91.