| Prototype Socio-Economic Scenarios for Climate change Strategic Management | 01/12/2021 | RFP-T016 | RFP-T016 (945.48 Kb) |
| Accelerator Trial Update 2021 | 01/12/2021 | RFP-T015 | RFP-T015 (2.07 Mb) |
| Capture and extraction of phenotypic traits from novel high-density point clouds | 01/12/2021 | RFP-T014 | RFP-T014 (2.21 Mb) |
| Social Extension of Quantitative Portfolio Framework | 24/06/2021 | RFP-T013 | RFP-T013 (489.16 Kb) |
| Towards quantitative analysis of social risk in forest planning | 24/06/2021 | RFP-T012 | RFP-T012 (525.30 Kb) |
| Risk perception and climate change adaptation: initial survey results using Protection Motivation Theory approach | 24/06/2021 | RFP-T010 | RFP-T010 (1023.95 Kb) |
| Identifying the key pathosystem components of red needle cast | 15/06/2021 | RFP-T011 | RFP-T011 (1.42 Mb) |
| Enterprise Risk management framework | 24/05/2021 | RFP-T009 | RFP-T009.doc (928.33 Kb) |
| Nursery automation and phenotyping: final report | 26/09/2020 | RFP-T006 | RFP-T006 (3.77 Mb) |
| Use of hyperspectral imagery to predict foliar nitrogen, phosphorus and photosynthetic capacity in radiata pine | 26/09/2020 | RFP-T004 | RFP-T004 (1.10 Mb) |
| Predicting Estate Productivity using Area-Based Phenotyping and Machine Learning | 07/07/2020 | RFP-T007 | RFP-T007 (703.33 Kb) |
| Red Needle Cast monitoring framework using high resolution satellite imagery | 16/06/2020 | RFP-T008 | RFP-T008 (4.10 Mb) |
| Identifying Key Parameter for RNC Severity Modelling and Prediction | 26/04/2020 | RFP-T005 | RFP-T005 (805.67 Kb) |
| Monitoring the seasonal growth impact of foliar pathogens – an ideal sensor network | 20/04/2020 | RFP-T003 | RFP-T003 (1.15 Mb) |
| Needs of stakeholders and state-of-the-art in tree and forest growth simulation | 20/04/2020 | RFP-T002 | RFP-T002 (1.70 Mb) |
| Review of literature on the development of climatic and socio-economic scenarios for New Zealand forestry | 20/04/2020 | RFP-T001 | RFP-T001 (1.37 Mb) |
| FGR Nursery Automation: Interim update | 20/11/2019 | RFP-T000 | RFP-T000 (1.41 Mb) |
