| || || Nand, Moleen Monita|
| || || Evaluating the impacts of climate change and climate variability on potato production in Banisogosogo, Fiji|
Author:Nand, Moleen Monita
Institution: University of the South Pacific.
Subject: Potatoes -- Climatic factors -- Fiji -- Ra Province, Potatoes -- Effect of global warming on -- Fiji -- Ra Province
Call No.: pac SB 211 .P8 N362 2013
Copyright:20-40% of this thesis may be copied without the authors written permission
Abstract: This research evaluated how climate change and climate variability affects potato production in Fiji. It also investigated which crop management strategies optimised potato yield in both current and future climate scenario. The study was conducted using the Decision Support System for Agrotechnology Transfer (DSSAT) v4.5 SUBSTOR Potato model. Three experimental replicate plots using the cultivar Desiree were located in Banisogosogo, Fiji. The values for LAI, fresh and dry weight of aboveground and belowground plant components (stem, leaves, roots and tubers) were taken for four progressive harvest (T1, T2, T3 and T4). Prior to the calibration process, the model’s simulated values did not agree the observed values. This was because the model had never been tested in the Tropics for Desiree variety. The DSSAT SUBSTOR Potato model was calibrated using the local experimental field data, local soil and weather data of the growing season. The calibration steps involved the recalculation of soil water content and the recalibration of genetic-coefficient to suit the temperature and daylength regime similar to the experimental conditions. The value for R2 for replicate plot 1, replicate plot 2 and replicate plot 3 were R2= 0.88, R2= 0.66 and R2= 0.92 respectively. The calibration showed that the simulated data was in good agreement with the observed data. The DSSAT SUBSTOR Potato model was simulated under current climate conditions for Banisogosogo, Koronivia and Nacocolevu using Desiree variety. The three locations gave different tuber yield. The potential yield obtained for Banisogosogo, Koronivia and Nacocolevu were 5561 kg/ha, 9811 kg/ha and 8347 kg/ha respectively while the non-potential yield for Banisogosogo, Koronivia and Nacocolevu were 4478 kg/ha, 4373 kg/ha and 5405 kg/ha respectively. Other significant findings to emerge from this simulation was that the optimum row spacing should be 30 cm or 40 cm and the optimum planting depth of 1.5 cm or 2 cm is required to optimise the yield. Likewise, under climate variability simulation, the percentage difference for tuber dry yield shows variation. Neutral year gave the highest yield for Banisogosogo and Nacocolevu (3527.85 kg/ha and 2880 kg/ha respectively) with El Niño giving a percentage difference of 61.4% and 29.94% respectively. On the other hand, El Niño provided the highest yield for Koronivia (4465.2 kg/ha) with La Niña providing a percentage difference of 31.19%. Furthermore, future climate simulations were also xxi conducted with Pacific Climate Change Science Programme for medium (A1B) and high (A2) emission scenarios for 2030, 2055 and 2090 using Desiree for the three locations. The three locations showed a similar trend. Under future emission scenarios, the LAI and the tuber initiation day increased while the tuber production (tuber dry and fresh weight) decreased. Under Banisogosogo future climate simulations, no tuber yield was noticed under 2055 potential simulation and 2090 simulations for A1B and A2 emission scenario. Koronivia simulations indicated that no tuber yield was noticed under 2090 potential simulation for A1B and A2 emission scenario while under Nacocolevu simulations, the tuber yield was possible under all emission scenario. The optimisation treatments indicated that optimum planting depth of 1.5 cm or 4 cm is required to optimise yield. Simulations were also conducted for Sebago and Russet Burbank variety. This simulation indicated that Sebago gave higher yields under current and future climate scenario whereas Russet Burbank gave zero or negligible yield under future climate scenario.