Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Flood related loss and recovery of intertidal seagrass meadows in southern Queensland, Australia

The loss and recovery of intertidal seagrass meadows were assessed following the flood related catastrophic loss of seagrass meadows in February 1999 in the Sandy Strait, Queensland. Region wide recovery rates of intertidal meadows following the catastrophic disturbance were assessed by mapping seagrass abundance in the northern Great Sandy Strait region prior to and on 3 occasions after widespread loss of seagrass. Meadow-scale assessments of seagrass loss and recovery focussed on two existing Zostera capricorni monitoring meadows in the region. Mapping surveys showed that approximately 90% of intertidal seagrasses in the northern Great Sandy Strait disappeared after the February 1999 flooding of the Mary River. Full recovery of all seagrass meadows took 3 years. At the two study sites (Urangan and Wanggoolba Creek) the onset of Z. capricorni germination following the loss of seagrass occurred 14 months post-flood at Wanggoolba Creek, and at Urangan it took 20 months for germination to occur. By February 2001 (24 months post-flood) seagrass abundance at Wanggoolba Creek sites was comparable to pre-flood abundance levels and full recovery at Urangan sites was complete in August 2001 (31 months post-flood). Reduced water quality characterised by 2–3 fold increases in turbidity and nutrient concentrations during the 6 months following the flood was followed by a 95% loss of seagrass meadows in the region. Reductions in available light due to increased flood associated turbidity in February 1999 were the likely cause of seagrass loss in the Great Sandy Strait region, southern Queensland. Although seasonal cues influence the germination of Z. capricorni, the temporal variation in the onset of seed germination between sites suggests that germination following seagrass loss may be dependent on other factors (eg. physical and chemical characteristics of sediments and water). Elevated dissolved nitrogen concentrations during 1999 at Wanggoolba Creek suggest that this site received higher loads of sediments and nutrients from flood waters than Urangan. The germination of seeds at Wanggoolba Creek one year prior to Urangan coincides with relatively low suspended sediment concentrations in Wanggoolba Creek waters. The absence of organic rich sediments at Urangan for many months following their removal during the 1999 flood may also have inhibited seed germination. Data from population cohort analyses and population growth rates showed that rhizome weight and rhizome elongation rates increased over time, consistent with rapid growth during increases in temperature and light availability from May to October

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Better Macadamia crop forecasting

Better Macadamia crop forecasting.

Better Macadamia Crop Forecasting - Part 2

The continually expanding macadamia industry needs an accurate crop forecasting system to allow it to develop effective crop handling and marketing strategies, particularly when the industry faces recurring cycles of unsustainably high and low commodity prices. This project aims to provide the AMS with a robust, reliable predictive model of national crop volume within 10% of the actual crop by 1 April each year by factoring known seasonal, environmental, cultural, climatic, management and biological constraints, together with the existing AMS database which includes data on tree numbers, tree age, variety, location and previous season's production.

Soil seed bank dynamics in response to an extreme flood event in a riparian habitat

A significantly increased water regime can lead to inundation of rivers, creeks and surrounding floodplains- and thus impact on the temporal dynamics of both the extant vegetation and the dormant, but viable soil-seed bank of riparian corridors. The study documented changes in the soil seed-bank along riparian corridors before and after a major flood event in January 2011 in southeast Queensland, Australia. The study site was a major river (the Mooleyember creek) near Roma, Central Queensland impacted by the extreme flood event and where baseline ecological data on riparian seed-bank populations have previously been collected in 2007, 2008 and 2009. After the major flood event, we collected further soil samples from the same locations in spring/summer (November–December 2011) and in early autumn (March 2012). Thereafter, the soils were exposed to adequate warmth and moisture under glasshouse conditions, and emerged seedlings identified taxonomically. Flooding increased seed-bank abundance but decreased its species richness and diversity. However, flood impact was less than that of yearly effect but greater than that of seasonal variation. Seeds of trees and shrubs were few in the soil, and were negatively affected by the flood; those of herbaceous and graminoids were numerous and proliferate after the flood. Seed-banks of weedy and/or exotic species were no more affected by the flood than those of native and/or non-invasive species. Overall, the studied riparian zone showed evidence of a quick recovery of its seed-bank over time, and can be considered to be resilient to an extreme flood event.