Tom Mahony received his M.S. degree in Natural Resources with a thesis focus in Plant Ecology from HumboldtStateUniversity in 1999. He has spent 24 years working with California vegetation and habitats, specializing in biotic assessments, wetland delineations, special-status plant surveys, vegetation classification/mapping, mitigation planning, and ecological restoration. He is a Certified Professional Wetland Scientist (PWS #2567) and holds a Plant Voucher Collecting Permit (No. 2081(a)-17-100-V) from the California Department of Fish and Wildlife.
Mr. Mahony is trained in wetland delineation procedures required under Section 404 of the Clean Water Act, Section 10 of the Rivers and Harbors Act, and the California Coastal Act, and has conducted wetland delineations throughout California for both private and public-sector clients. He has written wetland delineation reports and associated permit applications, including those for Corps of Engineers Nationwide Permits, Regional Water Quality Control Board Water Quality Certifications, and California Department of Fish and Wildlife Streambed Alteration Agreements. In addition, Mr. Mahony has expertise in wetland, riparian, and other Environmentally Sensitive Habitat Area delineations, biotic assessments, and buffer zone analyses required by the California Coastal Act. He has advanced training and extensive field experience identifying and mapping hydric soils.
Mr. Mahony has conducted numerous special-status plant surveys and botanical assessments utilizing methodologies approved by the California Native Plant Society, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service. He has managed mitigation monitoring projects in a wide variety of habitats. He has completed vegetation classifications in northwestern California, southwestern Oregon, and the Sierra Nevada foothills, and has published articles on vegetation classification. Mr. Mahony is trained in ecological analysis using GIS, GPS, and remote sensing techniques, and has developed vegetation prediction models for the National Park Service.