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.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Plant composition modulates arthropod pest and predator abundance: Evidence for culling exotics and planting natives

We investigate the role of plant species in crops, pasture and native vegetation remnants in supporting agronomic pests and their predators. The study was conducted in three Australian States and across 290 sites sampled monthly for two years. Pastures played a key role in harbouring pest species consistent across States, while native vegetation hosted relatively more predators than other habitat types within each State. Furthermore, native plant species supported the lowest pest density and more predators than pests; in contrast, 75 of the exotic weed species surveyed hosted more pests than predators. Despite the role of pasture in harbouring pests, we found in NSW that pasture also supported the highest proportion of juvenile predators, while native vegetation remnants had the lowest. Our results indicate that non-crop habitat (native remnants or pasture) with few exotic weeds supports high predator and low pest arthropod densities, and that weeds are associated with high pest densities. By linking broad response variables such as ‘all pests’ with specific predictors such as ‘plant species’, our study will inform on-farm management actions of which weeds to control and which natives to plant or regenerate. This study shows the importance of knowing the function of habitats and plants species in supporting pests and predators in agricultural landscapes across multiple regions.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Natural host range, thrips and seed transmission of distinct Tobacco streak virus strains in Queensland, Australia

Diseases caused by Tobacco streak virus (TSV) have resulted in significant crop losses in sunflower and mung bean crops in Australia. Two genetically distinct strains from central Queensland, TSV-parthenium and TSV-crownbeard, have been previously described. They share only 81% total-genome nucleotide sequence identity and have distinct major alternative hosts, Parthenium hysterophorus (parthenium) and Verbesina encelioides (crownbeard). We developed and used strain-specific multiplex Polymerase chain reactions (PCRs) for the three RNA segments of TSV-parthenium and TSV-crownbeard to accurately characterise the strains naturally infecting 41 hosts species. Hosts included species from 11 plant families, including 12 species endemic to Australia. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was both a natural host of, and experimentally infected by TSV-parthenium but this infection combination resulted in non-viable seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. TSV-crownbeard was seed transmitted from naturally infected crownbeard at a rate of between 5% and 50% and was closely associated with the geographical distribution of crownbeard in central Queensland. TSV-parthenium and TSV-crownbeard were also seed transmitted in experimentally infected ageratum (Ageratum houstonianum) at rates of up to 40% and 27%, respectively. The related subgroup 1 ilarvirus, Ageratum latent virus, was also seed transmitted at a rate of 18% in ageratum which is its major alternative host. Thrips species Frankliniella schultzei and Microcephalothrips abdominalis were commonly found in flowers of TSV-affected crops and nearby weed hosts. Both species readily transmitted TSV-parthenium and TSV-crownbeard. The results are discussed in terms of how two genetically and biologically distinct TSV strains have similar life cycle strategies in the same environment.

The growth, reproduction and survival of 'Cascabela thevetia' seedlings under two levels of canopy cover

The ornamental tree 'Cascabela thevetia', from tropical America, has naturalised and formed large infestations at several locations in northern Australia. Some understanding of its ecology and invasiveness was gleaned from a field experiment undertaken in North Queensland. The experiment quantified the growth, time to seed formation and survival of seedlings of the peach biotype growing under light and dense canopy cover within a riparian habitat. Growth, reproduction and survival of young plants varied. Growth was most rapid for seedlings away from, or on the edge of infestations because they were constrained by parent plants. The findings also suggested that land managers have at least 12 months following control to detect new plants, or regrowth, before plants set seed and replenish soil seed banks.

Green and brown bridges between weeds and crops reveal novel Diaporthe species in Australia

Diaporthe (syn. Phomopsis) species are well-known saprobes, endophytes or pathogens on a range of plants. Several species have wide host ranges and multiple species may sometimes colonise the same host species. This study describes eight novel Diaporthe species isolated from live and/or dead tissue from the broad acre crops lupin, maize, mungbean, soybean and sunflower, and associated weed species in Queensland and New South Wales, as well as the environmental weed bitou bush (Chrysanthemoides monilifera subsp. rotundata) in eastern Australia. The new taxa are differentiated on the basis of morphology and DNA sequence analyses based on the nuclear ribosomal internal transcribed spacer region, and part of the translation elongation factor-1α and ß-tubulin genes. The possible agricultural significance of live weeds and crop residues ('green bridges') as well as dead weeds and crop residues ('brown bridges') in aiding survival of the newly described Diaporthe species is discussed.