Overview of Impact Analysis

"Impact analysis" in the field of biosecurity refers to the systematic evaluation of the consequences—direct and indirect—caused by the incursion of invasive species on economic, environmental, and social aspects of a system. This analysis is critical for strategic planning and risk management to maintain biodiversity, safeguard public health, and uphold agricultural productivity. Understanding the impacts of potential biosecurity incursions can help make compelling business cases for increasing border protections and resourcing early detection surveillance.


Invasive species can have a profound economic impact on different sectors. They can trigger production losses, a decline in property value, job loss, and even price fluctuations. Regulations often demand freedom from pests and diseases, and detection of these regulated pests can lead to disruptions in domestic and international trade. These disruptions can further ripple into indirect impacts as consumers and producers adapt, for instance, by seeking substitute products.

Figure 1. Components of total economic value (TEV) (Born et al. 2005)

Non-market impacts can manifest as ecological damages, loss of biodiversity, and potential health consequences. Over time, these may translate into long-term economic implications, such as diminished land productivity, escalating healthcare costs, and depletion of potential pharmaceutical resources.


Impact analysis in biosecurity involves understanding the directionality, value bias, and scale of impacts. They could lead to losses, benefits, or both. For instance, a weed invasion may decrease biodiversity but enhance soil nutrients. Stakeholder perception also plays a role as different groups may place varying values on assets and services.


Impacts are measured using quantitative methods or classification systems. Quantitative methods might involve monetizing the value of goods and services, whereas classification systems like the Generic Impact Scoring System (GISS), the Environmental Impact Classification for Alien Taxa (EICAT), and the Socio-economic Impact Classification of Alien Taxa (SEICAT) assign rankings to impacts to assist prioritization.


Table 1. Impact related literature



Literature sources

Impact analysis approaches

Born et al. 2005; Epanchin-Niell and Hastings 2010; Lodge et al. 2009; Lodge et al. 2016; Marbuah et al. 2014; Olson 2006

Impact analysis as component of biosecurity management

Lodge et al. 2009; Fleming et al. 2017; Hulme 2006; Latombe et al. 2017; Robertson et al. 2020

Risk assessment with impact analysis to provide framework for biosecurity decision making 

Lodge et al. 2016; Hulme et al. 2012; Roy et al. 2018;  Soliman et al. 2010;  Soliman et al. 2015

RRRA risk return resource allocation model aims to allocate resources to maximise the reduction in risk

Craik et al. 2017

Cost – benefit analysis of biosecurity management or comparative analyses 

Born et al. 2005; Craik et al. 2017;  Boyd et al. 2015; Epanchin-Niell 2017; Faccoli and Gatto 2016; Fasina et al. 2012; Kompas et al. 2017; Dodd et al. 2020;  Hafi et al. 2015

Indirect costs

Born et al. 2005; Epanchin-Niell and Hastings 2010; Soliman et al. 2015; Holmes et al. 2009; Jeschke et al. 2014;  McDermott et al. 2013 

(CICES) common international classification of ecosystemservices & other classification schemes

Dodd et al. 2020; Haines-Young and Potschin 2012;  Haines-Young and Potschin 2013; Haines-Young and Potschin 2018; de Groot et al. 2002;  Pejchar and Mooney 2009

Distinctiveness or “Noah’s Ark Problem” - biodiversity

DAFF 2021;  Weitzman 1998; Arponen et al. 2005

Value measured by net primary production,

Costanza et al. 1998

Measures of “invasiveness” (a surrogate for impact)

O’Loughlin et al. 2019;  Aukema et al. 2011; Latombe et al. 2022; Parker et al. 1999

(GISS) Generic impact scoring system

Kumschinck et al. 2015; Nentwig et al. 2010

(EICAT) Environmental impact classification for alien taxa

Blackburn et al. 2014; Hawkins et al. 2015;  IUCN 2020;  Kumschick et al. 2020;  Volery et al. 2020;  Bacher et al. 2018; Ireland et al. 2020; Froese et al. 2021; Gruber et al. 2022

(SEICAT) Socio-economic impact classification of alien taxa

Bacher et al. 2018

(PPIMS) Plant pest impact metric system

Ireland et al. 2020  

(PB) partial budgeting

Lodge et al. 2016; Soliman et al. 2010; Soliman et al. 2015; McDermott et al. 2013; MacLeod et al. 2004

(PE) partial equilibrium 

Lodge et al. 2016; Soliman et al. 2010; Soliman et al. 2015; Cook et al. 2013;  Soliman et al. 2012; Welsh et al. 2021

(IO) input-output analysis

Lodge et al. 2016; Soliman et al. 2010; Soliman et al. 2015; McDermott et al. 2013; Elliston et al. 2004; Julia et al. 2007; Lui and Piper 2016 

(CGE) computable general equilibrium

Lodge et al. 2016; Soliman et al. 2010; Soliman et al. 2015; McDermott et al. 2013; Wittwer et al. 2005;  Finnoff and Tschirhart 2008

Frameworks with broader pest invasion (arrival, establishment, spread & impact) & bioeconomic modelling

Leung et al. 2002; Yemshanov et al. 2009; Kompas et al. 2017; Dodd et al. 2020; Cacho et al. 2008; Cook et al. 2013; Cook et al. 2013; Epanchin-Niell and Liebhold 2015;  Hester et al. 2013; Holmes et al. 2010; Kovacs et al. 2010;  Kovacs et al. 2011; Leung et al. 2012; Leung et al. 2014; Saphores and Shogren 2005; Susaeta et al. 2016; Yemshanov et al. 2017

(NPV) Net present value – future values are discounted to account for inflation

Marbuah et al. 2014; Olson 2006; Hulme et al. 2012; Soliman et al. 2015; Kompas et al. 2017;     Dodd et al. 2020; McDermott et al. 2013; Cook et al. 2013; Epanchin-Niell and Liebhold 2015;   Hester et al. 2013; Kovacs et al. 2010; Leung et al. 2014;  Epanchin-Niell et al. 2014; Kaiser 2006;  McIntosh et al. 2009; Sinden and Griffith 2007

Shifts in supply-demand curves – lead to changes in surplus values

Epanchin-Niell and Hastings 2010; Soliman et al. 2010; Soliman et al. 2015; Cook et al. 2013;   McIntosh et al. 2009; Sinden and Griffith 2007; Costanza et al. 1998   

Indirect valuation of non-market goods; i.e. willingness to play (WTP); hedonic pricing, factor income valuation etc

de Groot et al. 2002;  Adamowicz 2004;  Kaiser 2006; McIntosh et al. 2009;  McIntosh et al. 2010; Sinden and Griffith 2007

(SAWRMS)  South Australian weed risk managementsystem

Virtue 2010  

(NEWP) National Establishment Weed Priorities

Virtue et al. 2022  


Several complex bioeconomic approaches, including partial budgeting, partial equilibrium analysis, and computable general equilibrium modelling, can be employed in the process of impact analysis that can improve estimates of incursion-related value losses. They aim to compare potential damage costs against the cost of management response options. Moreover, assessing the value losses from incursions is critical. Direct-use market values are relatively straightforward to monetize, but valuing indirect-use and non-use goods often necessitates more complex methods such as contingent valuation, choice modelling, and replacement-based evaluation.


Biosecurity impact analysis often employs economic valuation or costing approaches that use net present values (NPV). These approaches discount future values to account for inflation and ensure present-time relevance. This way, we can compare the cost of impacts to the cost of actions taken against invasive species, helping us decide the most cost-effective way to manage biosecurity threats.


In the process of impact analysis, several economic modelling approaches may be employed. These range from simple fixed-price single sector models (Partial Budgeting, PB) to adaptive-pricing multi-sector models (Computable General Equilibrium, CGE). The latter combines adaptive pricing aspects of partial equilibrium (PE) models with the ability of input-output (IO) models to analyze impacts across multiple sectors.


Impact analysis with partial budgeting (PB) models assesses the immediate direct impacts of an invasive species incursion. Input-output (IO) models extend PB to analyze broader economic consequences across different sectors, acknowledging that changes in demand in one sector can affect others (a phenomenon known as the multiplier effect). Computable general equilibrium (CGE) models provide a more comprehensive analysis, estimating the total economic impacts across multiple sectors, considering both supply and demand adaptations and inter-sectoral commodity flows.


However, these models do have their limitations. Input-output (IO) models are limited in their focus on demand changes and short-term impacts, while computable general equilibrium (CGE) models, despite being comprehensive, are complex, time-consuming, and require significant expertise.


Figure 2. An example generalised workflow for impact analysis

To ensure a comprehensive bioeconomic analysis, these economic models are complemented by ecological models that simulate dynamic feedback mechanisms within and between ecological and economic components. In addition, multiple techniques, including decision trees, score-based systems, and matrix tools, are used to assess the impact of invasive species. These methods consider factors like the intensity, spatial extent, reversibility, and persistence of an invasion, the adaptability of the invader, and the number of species or habitats affected.


When sufficient data is available, classification systems such as the Environmental Impact Classification for Alien Taxa (EICAT) are used to assign a category indicating the expected magnitude of the impact from invasive species. These kinds of impact assessments contemplate both environmental and socio-economic impacts, informing prioritization of biosecurity efforts.


In essence, the process of impact analysis requires identification of the scope of the analysis, selection of the appropriate economic model, configuration of the spatial region, and definition of input parameters. The process concludes with the interpretation and potential comparison of results, thereby assisting in informed decision-making and risk management in biosecurity.

Step 1 – Review available evidence, knowledge, data & valuation methods

The first step in our spatial impact analysis is to select a grid/raster that defines the extent of the area you want included, the grid resolution (grid cell size) and coordinate reference system (CRS) by using the 'Add' button when 'Region' part of the left hand menu is selected. You can add a layer from 'My Results', 'My Datasets', 'Curated Datasets', or import / upload your own data (if uploading data, it would need to be in GeoTIFF format, with extent, resolution, and CRS defined within the file).

Step 2 – Select the grid / raster layer to represent where the pest occurs

From the 'Occurrence' part of the left hand menu click on the 'Add New Input' under the 'Occurrence raster*'. As above you can select a variety of different raster / grid layers.  The values for presence data should include 1's, 0's and NA values only. If the layer is the probability of occurrence from an SDM, risk map, or spread model, the values will vary between 0, and 1.  Larger grid cell values would be expected if the grid represents the density of pests expected to be found in each grid cell.

Occurrence type* Select if the occurrence dataset represents either presence, density, or probabilities 

Multiplier* The default value is 1, but any numeric multiplier could be used to multiply each grid cell value by the selected value.  This can be either transform the values to be uniformly higher or lower as wanted. 

Threshold*  This threshold will identify the number which will be applied to the occurrence raster after the multiplier is applied, and any grid cell value equal to or less than this numeric threshold will not be included in value calculations.  The default threshold value is zero.

Step 3 – Select the valuation type and select modelling options

Currently, two types of methods are available, “Monetary Impact” or “Non-monetary Impact”. Soon we will be adding 'Categorical impact', 'and 'Ranked Impact' methods.

Monetary Impact

Select the 'Monetary Impact' from the left part of the tree, and as you add spatial layers (grids/rasters) that have spatial asset values using the 'Add New Input' button the layer names will appear under the Monetary Impact on the left menu and will also show the layer name as a row entry in the 'Aspect' column of the 'Loss rates' table. Users may select one or many value layers, and the option to add the national asset value layers generated by CEBRA at the University of Melbourne. See below for a detailed description of the available CEBRA value layers (Stoeckl et al. 2023).

    'Asset value layers*' section of the input parameters section allow you to 'Add New Input'. As above you can select a variety of different raster / grid layers, but the CEBRA asset value layers can also be selected here. While you can base impact estimates on just one asset value layer, many analyses will use multiple layers represent the value of different assets found in each grid cell; 16 layers were used in the recent analysis by CEBRA (Stoeckl et al. 2023 and see below).

    Impact measure This just sets the context of the experiment which is most important when sharing the workflow with others. Measure used to quantify or classify each impact 'aspect' or layer, consistent with the valuation type. Monetary measure should specify the unit used (e.g. '$'). Default is '$'

    Management cost unit This provides context if a 'Management costs' layer is added, and is unit of measure for management costs. This will typically be the same unit as 'Impact Measures' and the drop down allow selection of either '$' (default), 'hours', 'none'

    Loss rates  This table has the column 'Aspect' which will be populated with value layer names as they are added and 'Loss rate' which is a number between 1 and 0 indicating how much of the value in that layer will be impacted by that kind of threat when the pest is present.

    Combine function*  The total impact will be calculated for each value layer (aspect) that is added, but you also have the option to combine the impact layers to create a total loss estimate across all value types using a 'sum' or you can select 'none' if you do not want a total impact calculated across all value types.

    Management costs Optional spatial layer raster or vector of management costs at each location specified by the 'region', measured in the unit specified in the 'context'. Default is NULL  

Non Monetary Impact

Select the 'Non Monetary Impact' from the left part of the tree, and as you add spatial layers (grids/rasters) that have spatial asset values using the 'Add New Input' button the layer names will appear under the Monetary Impact on the left menu and will also show the layer name as a row entry in the 'Aspect' column of both the 'Impact measure' table and the 'Loss rates' table. 

    'Asset value layers*section of the input parameters section allow you to 'Add New Input'. As above you can select a variety of different raster / grid layers, and examples of non-monetary layers include species richness, habitat condition etc.

    Impact measure This table has the column 'Aspect' which will be populated with value layer names as they are added and the column 'Measure' which just provides context to the layer name, i.e. index of condition, number of species etc. Measures used to quantify or classify each impact aspect, consistent with the valuation type. Non-monetary (quantitative) measures should specify the unit used.

    Management costs The unit of measure for management costs. This will typically be the same unit as 'Impact Measures'. One of '$' (default), 'hours', 'none'

    Loss rates  This table has the column 'Aspect' which will be populated with value layer names as they are added and 'Loss rate' which is a number between 1 and 0 indicating how much of the value in that layer will be impacted by that kind of threat when the pest is present.

    Combine function*  The total impact will be calculated for each value layer (aspect) that is added, but you also have the option to combine the impact layers to create a total loss estimate across all value types using a 'sum' or you can select 'none' if you do not want a total impact calculated across all value types. Many non-monetary value layers are in different kinds of measurement units and can not be combined, so none will often be appropriate. The other options to combine layers include 'sum', 'mean', 'median', 'max' and 'none'.

    Management costs Optional spatial layer raster or vector of management costs at each location specified by the 'region', measured in the unit specified in the 'context'. Default is NULL  


Step 4 – Evaluate the results, and change inputs or parameter settings as needed


Summary of biosecurity value layers available on the platform (Stoeckl et al. 2023)

Biosecurity Commons is looking to provide the building blocks to generate or reuse existing asset value layers.   It's noteworthy that the researchers highlight the universal applicability of their approach. The Australian value layers available on Biosecurity Commons were produced by the CEBRA team at the University of Melbourne and comprise 14 value grids where the spatially explicit value of 14 services is estimated in monetary terms using 2015 $AUD. See below for a table describing the data layers, and a summary of a paper outlining the creation and use of these layers. These layers provide an example of the kinds of data that can be used or generated within Biosecurity Commons, and provide an approach that could be used more widely. Furthermore, the asset-led framework used in the paper summarised below could be applied in various contexts beyond biosecurity, including disaster risk reduction and natural capital accounting. This approach also presents opportunities for economies of scale and the potential for a comprehensive 'all agencies, all hazards' approach to asset valuation and community resilience.

The values associated with different assets were estimated using various methods (see paper for details).


Table 2. A summary of the monetary $AUD asset value layers available on the platform and produced by CEBRA (Stoeckl et al. 2023).

Capitals, Asset Types,  Asset Classes used in the analysis with brief description.                         




Asset Type

Asset Class




Ecosystem Service





The average value of agricultural production (per area) for aggregated commodity groups (cropping, horticulture, livestock grazing (sheep, cattle) and livestock intensive (e.g. pigs, poultry)



The average value of logs produced (plantations and native forests)




The estimated (replacement cost) of food harvested. Poor proxy*

Water for 



Estimated value of ‘water’ that is purified (and/or that has sediment removed) by the natural environment (varies by type of vegetation), e.g. the benefit of having wetlands/mangroves and forests help purify water.






Estimated value of erosion control provided by the natural environment (varies by type of vegetation). e.g. the benefit of vegetation to prevent soils being eroded





Estimated value of flood control provided by the natural environment (varies by type of vegetation) e.g. the benefit of having vegetation which slows down flood waters so helps prevent damage to property

Genepool / 



Estimated value of habitat and gene pool provided by the natural environment (varies by type of vegetation)





Estimated value of carbon that is sequestered in the natural environment (varies by type of vegetation) 

Mediation of 

Soil / Air



Estimated value of air and soil purification by the natural environment (varies by type of vegetation) - e.g. the benefit of having toxins removed


Residents – 


Recreation /


Estimated aesthetic and recreational values associated with the environment, e.g. the extra ‘value’ that houses with nice views have, the benefit people gain from being able to go bushwalking or swimming, even when ‘free’. 

Residents – 


Existence / 


Estimated values associated with having the environment intact – even if there is never any intention to use it.  E.g. willingness to pay to preserve the environment for its own sake or for future generations

Non-Residents - 



Estimated tourism values associated with the environment 

Indigenous – 



Attempt to estimate Indigenous cultural values - Not available on Biosecurity Commons*





(Cats, Dogs, etc)



The average expenditure (within region) on domestic cats and dogs






The average expenditure (within region) on horses, excluding race horses




Dwellings / 



About one-quarter of the estimated ANNUALISED capital value of houses and utilities; conceptually equivalent to ¼ rental incomes.   We use ¼ since biosecurity pests do not pose a threat to all types of physical infrastructure.

*With the deepest respect we acknowledge the breadth and complexity of Indigenous cultural values and connections to country, discussed widely in bespoke literatures.  We conferred with Indigenous scholars, seeking advice as to whether it was better to omit reference to Indigenous values altogether, or to flag their importance, albeit inadequately.  We were encouraged to flag rather than ignore, thus do so in two ways:   First considering only subsistence/food values (here) second more broadly considering other Indigenous cultural values are acknowledged but are not available on Biosecurity Commons at this time.


Summary of paper on 16 asset value layers (Stoeckl et al. 2023)

The paper, "The monetary value of 16 services protected by the Australian National Biosecurity System: Spatially explicit estimates and vulnerability to incursions" (Stoeckl et al. 2023), provides spatially explicit estimations of the current value of 16 services safeguarded by the Australian biosecurity system and explores their vulnerability to biosecurity threats across Australia’s 56 natural resource management regions. Authors made use of transfer functions and market prices to estimate the value of the services associated with assets protected by the biosecurity system. The study estimates the aggregate value of 16 services protected by the Australian biosecurity system at approximately $250 billion per annum, with a potential range of $174 billion to $1.365 trillion. Nearly 90% of these values associated with ecosystem services tied to Australia's natural capital. The researchers adopted a method of analysis that takes into account both market and non-market values, which are vital for a holistic evaluation of the system. Interestingly, less than half of the identified values are closely linked with the market. Instead, about 60% of the values are associated with non-market environmental goods and services, which significantly contribute to social welfare but don't typically have an explicit price attached to them.


It elaborates on the concept of environmental biosecurity in Australia, which encompasses protection from pests and diseases that could harm not just the environment, but also social amenities. These amenities are further broken down into social, economic, and cultural aspects, including tourism, human infrastructure, and cultural assets.


The study introduces the concept of 'vulnerabilities', which refers to potential losses per hectare per annum that could result from incursions by pests such as weeds and invertebrates. The researchers found that urban regions generally have a higher vulnerability than remote regions, with several large, remote regions displaying heightened susceptibility to weed incursions.


One of the significant findings of the study is the identification of biosecurity threats to a wide range of 'assets', which can be of economic, environmental, or other types. By estimating the benefit flow from these protected assets and considering the potential decline in asset value that could occur due to biosecurity breaches, the study provides a systematic framework for assessing biosecurity impacts.


The complexities involved in estimating the total value of the biosecurity system are acknowledged, with the researchers emphasizing that their estimates do not provide the precise value of the biosecurity system. However, the spatially explicit estimates proposed by the study could be integrated into larger bioeconomic models to simulate the spread and monetary impact of various pests across time and space.


The study emphasizes the importance of considering a wide array of impacts on a diverse range of assets when assessing the values and impacts relevant to any nation's biosecurity system. Despite the acknowledged imperfections of their approach, the study represents a significant step forward, offering valuable information to policymakers.


The researchers have also categorized threats and assets based on monetary cost and benefit estimates, allowing the identification of the most and least understood threats and assets. The study's findings indicate that globally, over 16,000 species have established populations outside their native ranges, all of which pose potential biosecurity threats. It's emphasized that further research is necessary to fill knowledge gaps, particularly regarding the potential monetary value of threats to social or companion animal categories.


Overall, the authors used a combination of existing research, databases, and socioeconomic indicators to generate spatially explicit monetary estimates for different services protected by the Australian National Biosecurity System. The study results reveal that the Australian biosecurity measures protect a vast amount of economic value, much of which is not typically captured through the market, such as regulatory and non-use cultural services. The research underscores the need for a broader understanding of the economic value associated with biosecurity protections, particularly those related to non-market assets, and warns that the importance of biosecurity measures may be significantly understated in current research.






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