Invasive species and their impacts on agri-ecosystems: issues and solutions for restoring ecosystem processes

Fleming, Peter J. S.; Ballard, Guy; Reid, Nicholas; Tracey, John P.

doi:10.1071/rj17046

Cited by 38 publications

(31 citation statements)

References 65 publications

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“…For most invaded ecosystems, there are only anecdotal invasion curves and lag time estimates available for established and emerging weeds (Larkin 2012;Antunes and Schamp 2017;Sindel 2009;Victoria Government 2010;Fleming et al 2018). These time-line invasion indices are also often lacking at the regional and continental scales (e.g., Australia) despite the usefulness of such information for policy planning and management.…”

Section: Introductionmentioning

confidence: 99%

Lag times and invasion dynamics of established and emerging weeds: insights from herbarium records of Queensland, Australia

et al. 2021

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Herbarium records provide comprehensive information on plant distribution, offering opportunities to construct invasion curves of introduced species, estimate their rates and patterns of expansions in novel ranges, as well as identifying lag times and hence “sleeper weeds”, if any. Lag times especially have rarely been determined for many introduced species, including weeds in the State of Queensland, Australia as the trait is thought to be unpredictable and cannot be screened for. Using herbarium records (1850–2010), we generated various invasiveness indices, and developed simple invasion and standardised proportion curves of changes in distribution with time for ~ 100 established and emerging weed species of Queensland. Four major periods (decades) of increased weed spread (spikes) were identified: 1850s, 1900–1920, 1950–1960 and 2000–2010, especially for grasses and trees/shrubs. Many weeds with spikes in spread periods did so only 1–2 decadal times, except for a few species with higher spike frequencies > 6; the majority of these spikes occurred recently (1950–1990). A significant proportion (~ 60%) of Queensland’s weeds exhibit non-linear increase in spread with time, and hence have lag phases (mean: 45.9 years; range: 12–126 years); of these lag-phase species, 39% are “sleeper” weeds with > 50 years of lag time (mainly trees/shrubs and grasses). Twelve traits of invasiveness, including lag time and species-specific/historical factors were screened, of which frequency of invasion waves, spread rates and residence time were the main drivers of weeds’ distribution. The low predictive power of lag time on weed distribution suggests that retrospective analyses offer little hope for a robust generalisation to identify weeds of tomorrow.

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Section: Introductionmentioning

confidence: 99%

Lag times and invasion dynamics of established and emerging weeds: insights from herbarium records of Queensland, Australia

et al. 2021

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“…As a result, natural resource managers are using a variety of strategies to address the issue. While specific management techniques vary by species, the overall management of invasive species depends where on the invasion curve the species occurs [ 7 – 9 ; Fig 1 ]. One species that is near the end of the invasion curve and requires long-term management is the wild pig ( Sus scrofa ).…”

Section: Introductionmentioning

confidence: 99%

Stakeholder perspectives towards the use of toxicants for managing wild pigs

et al. 2021

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Wild pigs (Sus scrofa) are one of the most detrimental invasive mammals in the US. Lack of adequate population control has allowed pigs to become established across the landscape, causing significant ecological and economic damage. Given the need for additional tools for reducing wild pig populations, two toxicants, warfarin and sodium nitrite, are at the forefront of the discussion regarding future wild pig management. However, no research has examined stakeholders’ perspectives towards the use of toxicants in wild pig management. Given the lack of knowledge, our goal was to determine stakeholders’ perspectives towards the legal use of toxicants for managing wild pigs. We surveyed 1822 individuals from three stakeholder groups (hunters, farmers, and forestland owners) across Alabama during February 2018 using an online survey following the Tailored Design Method. All three stakeholder groups were generally supportive of toxicant use, though their views differed slightly by group. Furthermore, all stakeholder groups were supportive of toxicant purchasing and use regulations, while accidental water contamination, human health impact, and incorrect usage of a toxicant were stakeholders’ greatest concerns. These results indicate that these groups would likely be in support of using toxicants for wild pig management in Alabama and could be a model for other states or locations. Consequently, these results have direct implications for shaping policy and possible use of toxicants as a future wild pig management tool.

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“…A pest animal is defined as any animal that has or has the potential to have an adverse economic, environmental or social/cultural impact [8]. Pest animals have adverse effects on Australian agri-ecosystem as they cause significant crop damage, competing with native species for pasture or causing soil erosion, and acting as reservoirs for diseases.…”

Section: Introductionmentioning

confidence: 99%

Pest Animal's Detection and Habitat Identification in Low-resolution Airborne Thermal Imagery

Ulhaq¹,

Khan²

2020

Preprint

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Invasive species are significant threats to global agriculture and food security being the major causes of crop loss. An operative biosecurity policy requires full automation of detection and habitat identification of the potential pests and pathogens. Unmanned Aerial Vehicles (UAVs) mounted thermal imaging cameras can observe and detect pest animals and their habitats, and estimate their population size around the clock. However, their effectiveness becomes limited due to manual detection of cryptic species in hours of captured flight videos, failure in habitat disclosure and the requirement of expensive high-resolution cameras. Therefore, the cost and efficiency trade-off often restricts the use of these systems. In this paper, we present an invasive animal species detection system that uses cost-effectiveness of consumer-level cameras while harnessing the power of transfer learning and an optimised small object detection algorithm. Our proposed optimised object detection algorithm named Optimised YOLO (OYOLO) enhances YOLO (You Only Look Once) by improving its training and structure for remote detection of elusive targets. Our system, trained on the massive data collected from New South Wales and Western Australia, can detect invasive species (rabbits, Kangaroos and pigs) in real-time with a higher probability of detection (85–100 %), compared to the manual detection. This work will enhance the visual analysis of pest species while performing well on low, medium and high-resolution thermal imagery, and equally accessible to all stakeholders and end-users in Australia via a public cloud.

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Invasive species and their impacts on agri-ecosystems: issues and solutions for restoring ecosystem processes

Cited by 38 publications

References 65 publications

Lag times and invasion dynamics of established and emerging weeds: insights from herbarium records of Queensland, Australia

Lag times and invasion dynamics of established and emerging weeds: insights from herbarium records of Queensland, Australia

Stakeholder perspectives towards the use of toxicants for managing wild pigs

Pest Animal's Detection and Habitat Identification in Low-resolution Airborne Thermal Imagery

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