Resilient Forestry is widely trusted as a leader in ecological forest science. We recognise the responsibility and privilege associated with communicating science, and take great care to maintain our reputation as an unbiased source of ecological knowledge. We can provide technical review for documents your organization is preparing or evaluating, or we can develop a synthesis of the latest scientific knowledge to answer your ecological questions. We are transparent in communicating our sources, and can help you engage with the scientific knowledge base at whatever level you are comfortable.
As life-long learners, we are inspired and impassioned educators. We can communicate our findings in a wide variety of formats. Our presentations are clear and professional, and can be adapted to audiences ranging from large and public to intimate and private. We produce publication quality-reports and figures. One of our great joys is in leading in-person educational experiences. We would be happy to lead a guided tour of your property, answering any questions you may have about its ecology and management.
Collectively, Resilient Forestry staff have over 50 years of experience in field data collection. We are familiar with traditional forest inventory techniques, including forest stratification, sampling design, fixed/variable/nested plot designs, timber cruising, and botany surveys. We have established workflows for estimating volume/biomass and modeling growth and yield with popular tools such as SuperACE and FVS, as well as in-house tools.
We are perpetually driven to advance the boundaries of ecological knowledge. Resilient Forestry has relationships with research programs across multiple universities and is an active participant in academic ecological research. We pursue every opportunity to practice primary research, and maintain in-house capabilities of executing an ecological study in its entirety. We take pride in our thoughtful and innovative study designs, as well as their implementation and analysis. We can leverage a variety of statistical and machine learning approaches to generate novel insights to ecological questions.
Our Recent Science Projects