Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

The introduction and release of Chiasmia inconspicua and C. assimilis (Lepidoptera: Geometridae) for the biological control of Acacia nilotica in Australia

Two geometrid moths Chiasmia inconspicua and Chiasmia assimilis, identified as potential biological control agents for prickly acacia Acacia nilotica subsp. indica, were collected in Kenya and imported into quarantine facilities in Australia where laboratory cultures were established. Aspects of the biologies of both insects were studied and CLIMEX® models indicating the climatically favourable areas of Australia were developed. Host range tests were conducted using an approved test list of 74 plant species and no-choice tests of neonate larvae placed on both cut foliage and potted plants. C. inconspicua developed through to adult on prickly acacia and, in small numbers, Acacia pulchella. C. assimilis developed through to adult on prickly acacia and also in very small numbers on A. pulchella, A. deanei, A. decurrens, and A. mearnsii. In all experiments, the response on prickly acacia could be clearly differentiated from the responses on the non-target species. Both insects were approved for release in Australia. Over a three-year period releases were made at multiple sites in north Queensland, almost all in inland areas. There was no evidence of either insect's establishment and both colonies were terminated. A new colony of C. assimilis was subsequently established from insects collected in South Africa and releases of C. assimilis from this new colony were made into coastal and inland infestations of prickly acacia. Establishment was rapid at one coastal site and the insect quickly spread to other infestations. Establishment at one inland area was also confirmed in early 2006. The establishment in coastal areas supported a CLIMEX model that indicated that the climate of coastal areas was more suitable than inland areas.

Modelling environmental effects on phenology and canopy development of diverse sorghum genotypes

The ability to predict phenology and canopy development is critical in crop models used for simulating likely consequences of alternative crop management and cultivar choice strategies. Here we quantify and contrast the temperature and photoperiod responses for phenology and canopy development of a diverse range of elite Indian and Australian sorghum genotypes (hybrid and landrace). Detailed field experiments were undertaken in Australia and India using a range of genotypes, sowing dates, and photoperiod extension treatments. Measurements of timing of developmental stages and leaf appearance were taken. The generality of photo-thermal approaches to modelling phenological and canopy development was tested. Environmental and genotypic effects on rate of progression from emergence to floral initiation (E-FI) were explained well using a multiplicative model, which combined the intrinsic development rate (Ropt), with responses to temperature and photoperiod. Differences in Ropt and extent of the photoperiod response explained most genotypic effects. Average leaf initiation rate (LIR), leaf appearance rate and duration of the phase from anthesis to physiological maturity differed among genotypes. The association of total leaf number (TLN) with photoperiod found for all genotypes could not be fully explained by effects on development and LIRs. While a putative effect of photoperiod on LIR would explain the observations, other possible confounding factors, such as air-soil temperature differential and the nature of model structure were considered and discussed. This study found a generally robust predictive capacity of photo-thermal development models across diverse ranges of both genotypes and environments. Hence, they remain the most appropriate models for simulation analysis of genotype-by-management scenarios in environments varying broadly in temperature and photoperiod.