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.

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

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.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

Climate savvy grazing (Developing improved grazing and related practices to assist beef production enterprises across northern Australia to adapt to a changing and more variable climate)

There is uncertainty over the potential changes to rainfall across northern Australia under climate change. Since rainfall is a key driver of pasture growth, cattle numbers and the resulting animal productivity and beef business profitability, the ability to anticipate possible management strategies within such uncertainty is crucial. The Climate Savvy Grazing project used existing research, expert knowledge and computer modelling to explore the best-bet management strategies within best, median and worse-case future climate scenarios. All three scenarios indicated changes to the environment and resources upon which the grazing industry of northern Australia depends. Well-adapted management strategies under a changing climate are very similar to best practice within current climatic conditions. Maintaining good land condition builds resource resilience, maximises opportunities under higher rainfall years and reduces the risk of degradation during drought and failed wet seasons. Matching stocking rate to the safe long-term carrying capacity of the land is essential; reducing stock numbers in response to poor seasons and conservatively increasing stock numbers in response to better seasons generally improves profitability and maintains land in good condition. Spelling over the summer growing season will improve land condition under a changing climate as it does under current conditions. Six regions were included within the project. Of these, the Victoria River District in the Northern Territory, Gulf country of Queensland and the Kimberley region of Western Australia had projections of similar or higher than current rainfall and the potential for carrying capacity to increase. The Alice Springs, Maranoa-Balonne and Fitzroy regions had projections of generally drying conditions and the greatest risk of reduced pasture growth and carrying capacity. Encouraging producers to consider and act on the risks, opportunities and management options inherent in climate change was a key goal of the project. More than 60,000 beef producers, advisors and stakeholders are now more aware of the management strategies which build resource resilience, and that resilience helps buffer against the effects of variable and changing climatic conditions. Over 700 producers have stated they have improved confidence, skills and knowledge to attempt new practices to build resilience. During the course of the project, more than 165 beef producers reported they have implemented changes to build resource and business resilience.