WHIPPET: a novel tool for prioritizing invasive plant populations for regional eradication.

Large geographic areas can have numerous incipient invasive plant populations that necessitate eradication. However, resources are often deficient to address every infestation. Within the United States, weed lists (either state-level or smaller unit) generally guide the prioritization of eradication of each listed species uniformly across the focus region. This strategy has several limitations that can compromise overall effectiveness, which include spending limited resources on 1) low impact populations, 2) difficult to access populations, or 3) missing high impact populations of low priority species. Therefore, we developed a novel science-based, transparent, analytical ranking tool to prioritize weed populations, instead of species, for eradication and tested it on a group of noxious weeds in California. For outreach purposes, we named the tool WHIPPET (Weed Heuristics: Invasive Population Prioritization for Eradication Tool). Using the Analytic Hierarchy Process that included expert opinion, we developed three major criteria, four sub-criteria, and four sub-sub-criteria, taking into account both species and population characteristics. Subject matter experts weighted and scored these criteria to assess the relative impact, potential spread, and feasibility of eradication (major criteria) for 100 total populations of 19 species. Species-wide population scores indicated that conspecific populations do not necessarily group together in the final ranked output. Thus, priority lists based solely on species-level characteristics are less effective compared to a blended prioritization based on both species attributes and individual population and site parameters. WHIPPET should facilitate a more efficacious decision-making process allocating limited resources to target invasive plant infestations with the greatest predicted impacts to the region under consideration.

Identifying thresholds in the impacts of an invasive groundcover on native vegetation.

Impacts of invasive species are often difficult to quantify, meaning that many invaders are prioritised for management without robust, contextual evidence of impact. Most impact studies for invasive plants compare heavily invaded with non-invaded sites, revealing little about abundance-impact relationships. We examined effects of increasing cover and volume of the non-native herbaceous groundcover Tradescantia fluminensis on a temperate rainforest community of southern Australia. We hypothesised that there would be critical thresholds in T. fluminensis abundance, below which the native plant community would not be significantly impacted, but above which the community's condition would degrade markedly. We modelled the abundance-impact relationship from 83 plots that varied in T. fluminensis abundance and landscape context and found the responses of almost all native plant indicators to invasion were non-linear. Native species richness, abundance and diversity exhibited negative exponential relationships with increasing T. fluminensis volume, but negative threshold relationships with increasing T. fluminensis cover. In the latter case, all metrics were relatively stable until cover reached between 20 and 30%, after which each decreased linearly, with a 50% decline occurring at 75-80% invader cover. Few growth forms (notably shrubs and climbers) exhibited such thresholds, with most exhibiting negative exponential relationships. Tradescantia fluminensis biomass increased dramatically at > 80% cover, with few native species able to persist at such high levels of invasion. Landscape context had almost no influence on native communities, or the abundance-impact relationships between T. fluminensis and the plant community metrics. Our results suggest that the diversity of native rainforest community can be maintained where T. fluminensis is present at moderate-to-low cover levels.

Leaf trait co-ordination in relation to construction cost, carbon gain and resource-use efficiency in exotic invasive and native woody vine species.

BACKGROUND AND AIMS: Success of invasive plant species is thought to be linked with their higher leaf carbon fixation strategy, enabling them to capture and utilize resources better than native species, and thus pre-empt and maintain space. However, these traits are not well-defined for invasive woody vines. METHODS: In a glass house setting, experiments were conducted to examine how leaf carbon gain strategies differ between non-indigenous invasive and native woody vines of south-eastern Australia, by investigating their biomass gain, leaf structural, nutrient and physiological traits under changing light and moisture regimes. KEY RESULTS: Leaf construction cost (CC), calorific value and carbon : nitrogen (C : N) ratio were lower in the invasive group, while ash content, N, maximum photosynthesis, light-use efficiency, photosynthetic energy-use efficiency (PEUE) and specific leaf area (SLA) were higher in this group relative to the native group. Trait plasticity, relative growth rate (RGR), photosynthetic nitrogen-use efficiency and water-use efficiency did not differ significantly between the groups. However, across light resource, regression analyses indicated that at a common (same) leaf CC and PEUE, a higher biomass RGR resulted for the invasive group; also at a common SLA, a lower CC but higher N resulted for the invasive group. Overall, trait co-ordination (using pair-wise correlation analyses) was better in the invasive group. Ordination using 16 leaf traits indicated that the major axis of invasive-native dichotomy is primarily driven by SLA and CC (including its components and/or derivative of PEUE) and was significantly linked with RGR. CONCLUSIONS: These results demonstrated that while not all measures of leaf resource traits may differ between the two groups, the higher level of trait correlation and higher revenue returned (RGR) per unit of major resource need (CC) and use (PEUE) in the invasive group is in line with their rapid spread where introduced.

Downscaling Pest Risk Analyses: Identifying Current and Future Potentially Suitable Habitats for Parthenium hysterophorus with Particular Reference to Europe and North Africa.

Pest Risk Assessments (PRAs) routinely employ climatic niche models to identify endangered areas. Typically, these models consider only climatic factors, ignoring the 'Swiss Cheese' nature of species ranges due to the interplay of climatic and habitat factors. As part of a PRA conducted for the European and Mediterranean Plant Protection Organization, we developed a climatic niche model for Parthenium hysterophorus, explicitly including the effects of irrigation where it was known to be practiced. We then downscaled the climatic risk model using two different methods to identify the suitable habitat types: expert opinion (following the EPPO PRA guidelines) and inferred from the global spatial distribution. The PRA revealed a substantial risk to the EPPO region and Central and Western Africa, highlighting the desirability of avoiding an invasion by P. hysterophorus. We also consider the effects of climate change on the modelled risks. The climate change scenario indicated the risk of substantial further spread of P. hysterophorus in temperate northern hemisphere regions (North America, Europe and the northern Middle East), and also high elevation equatorial regions (Western Brazil, Central Africa, and South East Asia) if minimum temperatures increase substantially. Downscaling the climate model using habitat factors resulted in substantial (approximately 22-53%) reductions in the areas estimated to be endangered. Applying expert assessments as to suitable habitat classes resulted in the greatest reduction in the estimated endangered area, whereas inferring suitable habitats factors from distribution data identified more land use classes and a larger endangered area. Despite some scaling issues with using a globally conformal Land Use Systems dataset, the inferential downscaling method shows promise as a routine addition to the PRA toolkit, as either a direct model component, or simply as a means of better informing an expert assessment of the suitable habitat types.

Are high-impact species predictable? An analysis of naturalised grasses in northern Australia.

Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.

Possible impacts of the invasive plant Rubus niveus on the native vegetation of the Scalesia forest in the Galapagos islands.

Originally from Asia, Rubus niveus has become one of the most widespread invasive plant species in the Galapagos Islands. It has invaded open vegetation, shrubland and forest alike. It forms dense thickets up to 4 m high, appearing to displace native vegetation, and threaten the integrity of several native communities. This study used correlation analysis between a R. niveus cover gradient and a number of biotic (vascular plant species richness, cover and vegetation structure) and abiotic (light and soil properties) parameters to help understand possible impacts in one of the last remaining fragments of the Scalesia forest in Santa Cruz Island, Galapagos. Higher cover of R. niveus was associated with significantly lower native species richness and cover, and a different forest structure. Results illustrated that 60% R. niveus cover could be considered a threshold for these impacts. We suggest that a maximum of 40% R. niveus cover could be a suitable management target.