Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Genetic erosion and changes in distribution of sorghum (Sorghum bicolor L. (Moench)) landraces in north-eastern Ethiopia

Ethiopia is believed to be the centre of origin and domestication for sorghum, where sorghum remains one of the main staple crops. Loss of biodiversity is occurring at an alarming rate in Ethiopia and crops, including sorghum, have long been recognized as vulnerable to genetic erosion. A major collection of sorghum germplasm was made in 1973 by Gebrekidan and Ejeta from north-eastern Ethiopia. A new collection of landraces was made in 2003, and these were field evaluated at Sirinka in 2004 along with representative samples from the 1973 collection. Farmer surveys and soil and climate surveys were also performed. Preliminary analysis demonstrated that some important landraces have disappeared either locally or regionally in the past 30 years and many other landraces have become marginalized. Landraces which are less preferred in terms of agronomic value and end use, and introductions, have become increasingly important. Late maturing landraces were found to be particularly vulnerable, with a number disappearing altogether. Farmers have become more risk averse, and factors such as declining soil fertility, more frequent drought and unreliable rainfall, and increased pest infestation have contributed to a change in farmer landrace selection. Data are presented on the variability and unique characters of some of the Ethiopian landraces, and implications for conservation are discussed.

Migration of feral pigs (Sus scrofa) in rainforests of north Queensland: fact or fiction?

The Wet Tropics bioregion of north Queensland has been identified as an area of global significance. The world-heritage-listed rainforests have been invaded by feral pigs (Sus scrofa) that are perceived to cause substantial environmental damage. A community perception exists of an annual altitudinal migration of the feral-pig population. The present study describes the movements of 29 feral pigs in relation to altitudinal migration (highland, transitional and lowland areas). Feral pigs were sedentary and stayed within their home range throughout a 4-year study period. No altitudinal migration was detected; pigs moved no more than a mean distance of 1.0 km from the centre of their calculated home ranges. There was no significant difference between the mean (+/- 95% confidence interval) aggregate home ranges for males (8.7 +/- 4.3 km², n = 15) and females (7.2 +/- 1.8 km², n = 14). No difference in home range was detected among the three altitudinal areas: 7.2 +/- 2.4 km² for highland, 6.2 +/- 3.9 km² for transitional and 9.9 +/- 5.3 km² for lowland areas. The aggregate mean home range for all pigs in the present study was 8.0 +/- 2.4 km². The study also assessed the influence seasons had on the home range of eight feral pigs on the rainforest boundary; home ranges did not significantly vary in size between the tropical wet and dry seasons, although the mean home range in the dry season (7.7 +/- 6.9 km²) was more than twice the home range in the wet season (2.9 +/- 0.8 km²). Heavier pigs tended to have larger home ranges. The results of the present study suggest that feral pigs are sedentary throughout the year so broad-scale control techniques need to be applied over sufficient areas to encompass individual home ranges. Control strategies need a coordinated approach if a long-term reduction in the pig population is to be achieved.

Determining and quantifying components of an aquaculture soundscape.

Recirculating aquaculture systems have a unique anthropogenic-based soundscape which is characterized by the type of equipment utilized, the structural configuration of walls, tanks, equipment, the substrate the tanks are situated on and even the activities of the personnel operating the facility. The soundscape of recirculation facilities is inadequately understood and remains poorly characterized, although it is generally accepted that the dominant sounds found in such facilities are within the hearing range of fish. The objective of this study was to evaluate the soundscape in a recirculating aquaculture facility from an intra-tank perspective and determine how the soundscape is shaped by a range of characteristics within the facility. Sounds were recorded across an operating aquaculture facility including different tank designs. The sounds recorded fell within previously measured pressure level ranges for recirculating systems, with the highest maximum sound pressure level (SPL) recorded at 124 dB re 1 mu Pa-2/Hz (with an FFT bin width of 46.9 Hz, centered at 187.5 Hz). The soundscape within the tanks was stratified and positively correlated with depth, the highest sound pressure occurring at the base of the tanks. Each recording of the soundscape was dominated by a frequency component of 187.5 Hz (corresponding centre of the 4th 46.9 Hz FFT analysis bin) that produced the highest observed SPL Analysis of sound recordings revealed that this peak SPL was associated with the acoustic signature of the pump. The soundscape was also evaluated for impacts of tank hood position, time of day, transient sounds and airstone particle size types, all of which were found to appreciably influence sound levels and structure within the tank environment. This study further discusses the distinctiveness of the soundscape, how it is shaped by the various operating components and considers the aquaculture soundscape in relation to natural soundscapes found within aquatic tropical environments.

Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method

Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors

Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.