Aim 3 & 4 Integration

Aim 3 Analyze genetics of breeding and natural populations to discover alleles in genes – controlling important adaptation and mitigation traits that enable future tree breeding strategies – deliver deployment guidelines for genotypes suited for varied climatic conditions – maximize resiliency and reduce adverse impacts of climate change on productivity

Aim 3 Deliverables (with Aim 4 overlap) Uniform Response Function - Deployment tool – Productivity under future conditions – Risk (possibly through bootstraping?) Genotyping (long-term overlap with Aim I and 2) – Identify specific alleles that influence pine response to environmental signals – Characterize the frequency and distribution of those alleles in deployment populations to aid in modeling carbon/nitrogen/water cycling in plantations and in risk assessment and management.

Aim 4 Conduct comprehensive life cycle analyses of regional forest management systems – multi-scale policy and economic analysis of market and non-market forest benefits and services – to evaluate regional tradeoffs and interactions among policy, climate scenarios, carbon/water/ nutrient/energy footprints, forest management, and genetic deployment, – assess adoption of alternative approaches by private landowners

Aim 4 Deliverables (with Aim 3 overlap) Net present value (NPV) analysis and forecast of adaptive management impacts Assessment of landowners’ mitigation and adaptation strategies Estimates of economic losses from disturbance risks

Integration Aim 3 → Aim 4 – Forest productivity and distributions under different climate assumptions as they impact LCA – Risk assessment Aim 4 → Aim 3 – Economic tradeoffs between productivity and risk (economic weights to refine breeding objectives) – Assessing end user risk tolerance/avoidance as possible input into URF deployment tool

Action Items Continue discussion on inputs/outputs needed to add value to other Aims