Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Space allowances for confined livestock and their determination from allometric principles

The amount of space provided to animals governs important elements of their behaviour and, hence, is critical for their health and welfare. We review the use of allometric principles and equations to estimate the static space requirements of animals when standing and lying, and the space required for animals to feed, drink, stand-up and lie-down. We use the research literature relating to transportation and intensive housing of sheep and cattle to assess the validity of allometric equations for estimating space allowances. We investigated these areas because transportation and intensive housing provide points along a continuum in terms of the duration of confinement, (from hours to months) and spatial requirements are likely to increase with increasing duration of confinement, as animals will need to perform a greater behavioural repertoire for long-term survival, health and welfare. We find that, although there are theoretical reasons why allometric relationships to space allowances may vary slightly for different classes of stock, space allowances that have been demonstrated to have adverse effects on animal welfare during transportation correlated well with an inability to accommodate standing animals, as estimated from allometry. For intensive housing, we were able to detect a space allowance below which there were adverse effects on welfare. For short duration transportation during which animals remain standing, a space allowance per animal described by the allometric equation: area (m^2) = 0.020W^0.66, where W = liveweight (kg), would appear to be appropriate. Where it is desirable for all animals to lie simultaneously, then a minimum space allowance per animal described by the allometric equation: area (m^2) = 0.027W^0.66 appears to permit this, given that animals in a group time-share space. However, there are insufficient data to determine whether this allowance onboard a vehicle/vessel would enable animals to move and access food and water with ease. In intensive housing systems, a minimum space allowance per animal described by the allometric equation: area (m^2) = 0.033W^0.66 appears to be the threshold below which there are adverse effects on welfare. These suggested space allowances require verification with a range of species under different thermal conditions and, for transportation, under different conditions of vehicular/vessel stability. The minimum length of trough per animal (L in m) required for feeding and drinking can be determined from L = 0.064W^0.33, with the number of animals required to feed/drink simultaneously taken into account, together with any requirement to minimise competition. This also requires verification with a range of species. We conclude that allometric relationships are an appropriate basis for the formulation of space allowances for livestock.

Using automated supplementation systems to meet growth targets for grazing sheep

Remote drafting technology now available for sheep allows targeted supplementation of individuals within a grazing flock. This paper reports results of three experiments. Experiment 1 examined the weight change of Merino wethers allowed access to either lupin grain or whole cottonseed 0, 1, 2 or 7 days/week for 6 weeks. Experiment 2 examined the weight change of Merino wethers allowed access to either lupins or a sorghum + cottonseed meal (CSM) supplement 0, 2, 4 or 7 days/week for 8 weeks. Experiment 3 investigated the relationship between five allocations of trough space at the supplement self-feeders (5–50 cm/sheep) and the weight change of Merino wethers allowed access to lupins 1 day/week for 8 weeks. In all experiments, the Merino wethers had free access as a single group to drinking water and low quality hay in a large group pen and were allowed access to supplement once per day on their scheduled days of access. No water was available in the areas containing supplement, but one-way flow gates allowed animals to return to the group pen in their own time. There was a linear response in growth rate to increased frequency of access to lupins in Experiments 1 and 2, with each additional day of access increasing liveweight gain by 26 and 21 g/day, respectively. Similarly, the response to the sorghum + CSM supplement was linear, although significantly lower (P < 0.05), at 12 g/day. Providing access to whole cottonseed resulted in no significant change in growth rate compared with the control animals. In Experiment 3, decreasing trough space from 50 to 5 cm/sheep had no effect on sheep liveweight change. It was concluded that the relationships developed here, for growth response to increased frequency of access to lupins or a sorghum + CSM supplement, could be used to indicate the most appropriate frequency of access to supplement, through a remote drafting unit, to achieve sheep weight change targets. Also, that a trough space of 5 cm/sheep appears adequate in this supplementation system.

Assessing the sustainability of wheat-based cropping systems using APSIM: Model parameterisation and evaluation

Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998-99 and 1999-2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM's cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat-fallow and wheat-chickpea rotations (1987-98) were nevertheless well simulated when the soil water content in 0-0.45 m soil depth was set to 'air dry' at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH 4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM's nitrogen module. APSIM was capable of predicting long-term trends (1985-98) in soil organic matter in wheat-fallow and wheat-chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the sustainability of wheat-chickpea rotations at Tel Hadya.

A participatory systems approach to understanding climate adaptation needs

Emerging literature on climate adaptation suggests the need for effective ways of engaging or activating communities and supporting community roles, coupled with whole-of-system approaches to understanding climate change and adaptation needs. We have developed and evaluated a participatory approach to elicit community and stakeholder understanding of climate change adaptation needs, and connect diverse community members and local office bearers towards potential action. The approach was trialed in a series of connected social-ecological systems along a transect from a rural area to the coast and islands of ecologically sensitive Moreton Bay in Queensland, Australia. We conducted ‘climate roundtables’ in each of three areas along the transect, then a fourth roundtable reviewed and extended the results to the region as a whole. Influence diagrams produced through the process show how each climate variable forecast to affect this region (heat, storm, flood, sea-level rise, fire, drought) affects the natural environment, infrastructure, economic and social behaviour patterns, and psychosocial responses, and how sets of people, species and ecosystems are affected, and act, differentially. The participatory process proved effective as a way of building local empathy, a local knowledge base and empowering participants to join towards future climate adaptation action. Key principles are highlighted to assist in adapting the process for use elsewhere.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.