Practical guidelines for modelling post-entry spread in invasion ecology

In this article we review a variety of methods to enable understanding and modelling the spread of a pest or pathogen post-entry. Building upon our experience of multidisciplinary research in this area, we propose practical guidelines and a framework for model development, to help with the application of mathematical modelling in the field of invasion ecology for post-entry spread. We evaluate the pros and cons of a range of methods, including references to examples of the methods in practice. We also show how issues of data deficiency and uncertainty can be addressed. The aim is to provide guidance to the reader on the most suitable elements to include in a model of post-entry dispersal in a risk assessment, under differing circumstances. We identify both the strengths and weaknesses of different methods and their application as part of a holistic, multidisciplinary approach to biosecurity research

Tropical cyclones and the ecohydrology of Australia's recent continental-scale drought

The Big Dry, a recent drought over southeast Australia, began around 1997 and continued until 2011. We show that between 2002-2010, instead of a localized drought, there was a continent-wide reduction in water storage, vegetation and rainfall, spanning the northwest to the southeast of Australia. Trends in water storage and vegetation were assessed using Gravity Recovery and Climate Experiment (GRACE) and Normalized Difference Vegetation Index (NDVI) data. Water storage and NDVI are shown to be significantly correlated across the continent and the greatest losses of water storage occurred over northwest Australia. The frequency of tropical cyclones over northwest Australia peaked just prior to the launch of the GRACE mission in 2002. Indeed, since 1981, decade-scale fluctuations in tropical cyclone numbers coincide with similar variation in rainfall and vegetation over northwest Australia. Rainfall and vegetation in southeast Australia trended oppositely to the northwest prior to 2001. Despite differences between the northwest and southeast droughts, there is reason to believe that continental droughts may occur when the respective climate drivers align

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Neighbourhood rules make or break spatial scale invariance in a classic model of contagious disturbance

Scale invariant patterns have been observed in a range of terrestrial and marine ecosystems. These patterns are commonly interpreted as a signature of a self-organising system where global structures emerge from local dynamic interactions between system elements. In effect, an analogy is drawn to the scale invariant output of self-organised model systems, such as the Drossel and Schwabl forest fire model (FFM), and scale invariance in actual systems is then taken to be the product of self-organisation rather than some other process-specific, generative cause. Misinterpretation of the generative mechanism of scale invariance may well have significant consequences for ecosystem management. In actual ecosystems spatial interactions typically vary in form, distance and direction over time, often dependent on exogenous factors such as weather. While simulation models may sometimes represent spatial processes using a variable interaction within a local neighbourhood, what influence this has on model phenomena that are normally attributable to self-organisation has been little studied. We relax a key assumption implicit in the FFM by allowing different sized neighbourhoods over which contagion can occur, rather than maintain a constant sized neighbourhood. We examine how the scaling behaviour of simulated fire sizes changes with a variable neighbourhood size, and show that the invariant scaling typical of the FFM ‘breaks’ with the relaxation of the neighbourhood assumption. Our findings are a strong indication that the generative origins of scale invariance in the FFM (i.e., self-organisation) and in actual fire-prone forest landscapes are essentially different, in contrast to conclusions of previous studies

Choosing the battles : the economics of area wide pest management for Queensland fruit fly

“Surely the best way to meet the enemy is head on in the field and not wait till they plunder our very homes” Oliver Goldsmith (1730–1774). Area-wide management (AWM) of crop pests is an alternative strategy for pest control to reliance on the uncoordinated control decisions of farmers. Relative to uncoordinated pest control, AWM has been shown to be cost-effective and, by reducing pesticide use, environmentally beneficial. The fact that AWM schemes provide imperfect public goods and are prone to free-riding means that most successful schemes depend on government funding, regulation, coordination and management. The economics of AWM concerns the economics of information and time in complex bioeconomic settings. This paper explores the economics of AWM in relation to Queensland fruit fly (Qfly), Bactrocera tryoni (Frogatt), a damaging pest and a major barrier to Australian trade in horticultural produce. We analyse the economics of roadblocks, surveillance and eradication. The results show that returns from tighter roadblocks are greater than returns from increased surveillance and enhanced eradication capacity. These results depend on market access rules, the spatial extent of the pest free area, the horticultural commodities at risk, and pest ecology.11 page(s

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1mquadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands

Spatial scale invariance of southern Australian forest fires mirrors the scaling behaviour of fire-driving weather events

Power law frequency-size distributions of forest fires have been observed in a range of environments. The scaling behaviour of fires, and more generally of landscape patterns related to recurring disturbance and recovery, have previously been explained in the frameworks of self-organized criticality (SOC) and highly optimized tolerance (HOT). In these frameworks the scaling behaviour of the fires is the global structure that either emerges spontaneously from locally operating processes (SOC) or is the product of a tuning process aimed at optimizing the trade-offs between system yield and tolerance to risks (HOT). Here, we argue that the dominant role of self-organized or optimised fuel patterns in constraining unplanned-fire sizes, implicit in the SOC and HOT frameworks, fails to recognise the strong exogenous controls of fire spread (i.e. by weather, terrain, and suppression) observed in many fire-prone landscapes. Using data from southern Australia we demonstrate that forest fire areas and the magnitudes of corresponding weather events have distributions with closely matching scaling exponents. We conclude that the spatial scale invariance of forest fires may also be a mapping of the meteorological forcing pattern

Spatial scale invariance of southern Australian forest fires mirrors the scaling behaviour of fire-driving weather events

Power law frequency-size distributions of forest fires have been observed in a range of environments. The scaling behaviour of fires, and more generally of landscape patterns related to recurring disturbance and recovery, have previously been explained in the frameworks of self-organized criticality (SOC) and highly optimized tolerance (HOT). In these frameworks the scaling behaviour of the fires is the global structure that either emerges spontaneously from locally operating processes (SOC) or is the product of a tuning process aimed at optimizing the trade-offs between system yield and tolerance to risks (HOT). Here, we argue that the dominant role of self-organized or optimised fuel patterns in constraining unplanned-fire sizes, implicit in the SOC and HOT frameworks, fails to recognise the strong exogenous controls of fire spread (i.e. by weather, terrain, and suppression) observed in many fire-prone landscapes. Using data from southern Australia we demonstrate that forest fire areas and the magnitudes of corresponding weather events have distributions with closely matching scaling exponents. We conclude that the spatial scale invariance of forest fires may also be a mapping of the meteorological forcing pattern

Long-term impacts of prescribed burning on regional extent and incidence of wildfires : evidence from 50 years of active fire management in SW Australian forests

Prescribed burning is advocated for the sustainable management of fire-prone ecosystems for its capacity to reduce fuel loads and mitigate large high-intensity wildfires. However, there is a lack of comprehensive field evidence on which to base predictions of the benefits of prescribed burning for meeting either wildfire hazard reduction or conservation goals. Australian eucalypt forests are among the very few forest types in the world where prescribed burning has been practised long enough and at a large enough spatial scale to quantify its effect on the incidence and extent of unplanned fires. Nevertheless even for Australian forests evidence of the effectiveness of prescribed burning remains fragmented and largely unpublished in the scientific literature. We analysed a 52-year fire history from a eucalypt forest region in south-western Australia to quantify the impact of prescribed burning on the incidence, extent and size distribution of wildfires. Quantile regression identified the longevity of the influence of prescribed fire treatments on wildfire incidence and extent. Anomalies in the frequency-size distribution of unplanned fires were identified through a relative risk mapping using kernel density estimates. Changes in the spatial distribution of fuel age were quantified using patch metrics, while generalized additive models were applied to estimate effects of fuel age patterns on the incidence and extent of unplanned fire