bioRxiv2024
1.Executive summaryIt is well known that the increasing globalisation of human movement and trade has led to substantial range expansions of many taxa, and as a consequence, is increasingly exposing countries to novel biosecurity threats. This increased exposure to novel threats is expected to be exacerbated by a changing climate as trade patterns and species distributions change. In many countries biosecurity regulators are already struggling to contend with the increased exposure to pests and diseases, and as such, must shift towards a pro-active strategy of anticipating risk. However, to anticipate risk, regulators must make better use of the data they collect (e.g. border interceptions) and develop models capable of forecasting biosecurity propagule pressure and establishment exposure as a function of changing trade, human population, and species distributions. In this project, we develop a highly innovative model framework that simulates annual changes in international trade patterns (imports & exports) as a function of climate change impacts on crop productivity, labour productivity (via heat stress) and the amount of arable land. These simulated changes in global trade are then coupled with border interception data, and annual predicted changes in the geographic distributions of both human populations and threat climate suitability to estimate climate-induced changes in: 1) contamination rates for imports from different trading partners, 2) the total amount of biosecurity risk material arriving at Australias borders, and 3) its exposure to an establishment event (Figure 1.1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/601437v1_fig1_1.gif" ALT="Figure 11"> View larger version (32K): org.highwire.dtl.DTLVardef@1755bcforg.highwire.dtl.DTLVardef@1de8225org.highwire.dtl.DTLVardef@1324d1forg.highwire.dtl.DTLVardef@16530e3_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.1.:C_FLOATNO Conceptual diagram of innovative biosecurity forecasting model. The model is made up of two primary sub-modules: 1) The Economic submodel, which incorporates climate change damages (e.g. crop productivity & heat stress) and simulates these impacts on global import and export trade patterns; 2) The Ecological submodel that estimates threat climate suitability, country-by-commodity contamination rates, and then links these to predicted changes in both global trade flows (i.e. outputs from the Economic submodel) and human population to approximate country-specific propagule pressure and establishment exposure. C_FIG Here, we provide an in-depth description of both the trade and biosecurity risk sub-models. We then illustrate the models implementation and outputs under two different climate scenarios (RCP 4.5 and RCP 8.5) for the purposes of forecasting temporal changes in: 1) global and regional economic trade; and 2) the amount of biosecurity risk material arriving at Australias border (i.e. propagule pressure) and what it may mean for establishment exposure. In illustrating the biosecurity risk, we focused on five plant pests deemed by the Department of Agriculture, Fisheries and Forestry (DAFF) as an exemplar of different hitch-hiking functional groups. The exemplar threats examined were: O_LIOverwintering - brown marmorated stink bug (BMSB; Halyomorpha halys) C_LIO_LIEgg laying - Spongy moth (Lymantria dispar) C_LIO_LINesting - Asian honey bee (Apis cerana) C_LIO_LISheltering - Giant African snail (Lissachatina fulica) C_LIO_LIInternal storage - Khapra beetle (Trogoderma granarium). C_LI 2. Key findings & model utility2.1. Global and regional economic trade consequences of climate changeThe climate-enhanced trade model shows significant changes in trade patterns globally. Climate change impacts various countries differently, causing substantial changes in national incomes, productive capacity, and imports and exports around the world. This occurs even with relatively limited damage functions from global warming. Indeed, with limited damage functions (crop productivity losses, labour productivity losses due to heat stress, and loss of arable land from ocean inundation), the impact on national income in Australia from climate change is relatively small (e.g., damages from more substantive sea level rise and storm surge are not included). However, damages to trading partners and changes in imports to Australia, as well as the rest of the world, are considerable. To allow for easy interrogation of these predicted trade impacts, we have developed an interactive dashboard1 that allows users to examine changes in trade patterns - by country, commodity and climate change scenario - for user selected imports by country and total values. The following summarise the key findings from the select damage functions employed within this analysis: O_LIWestern African regions fare the worst in terms of overall GDP impacts, with the region at large experiencing roughly a 20% loss to GDP. The second most affected region is South Asia2 with Pakistan bearing the greatest damages. Some countries emerged relatively unscathed, prominently those located in North America, Europe, Russia, and Oceania. C_LIO_LIIn terms of climate change related damages to key Australian trading partners, we find that losses in China and Southeast Asia3 are the most consequential. Here labour productivity shocks due to heat stress lead to losses in manufacturing sector imports such as Motor vehicles and Electronic equipment. As the largest exporter of manufacturing goods and a key region affected by climate change, China sees the largest decline in exports, however most of South and Southeast Asia fares worse in terms of relative losses with India and Indonesia seeing over 10% losses. Conversely, net gains are made across several European regions, particularly Germany and the UK. C_LIO_LIThe greatest heterogeneity within macroeconomic sector was observed among agricultural imports and in particular crop sectors in large part due to the varied mix of exporters for each crop type and differential impacts experienced. The largest absolute increase among food- and agriculture-related sectors is seen within Vegetables, fruit, nuts with large increases in exports from OECD regions and China. C_LIO_LIThe climate change damage functions employed here likely vastly underestimate the true costs of climate change impacts for a number of reasons. These include the following: O_LIRecent scholarship suggests that large damages to GDP are already being experienced (Romanello et al., 2023) whereas the earlier work used here (with the exception of crop productivity) includes minimal damages at early timesteps. Further, the anticipated impacts from warming may be far larger (particularly at later timesteps) if climate sensitivities have been misestimated (leading to more extreme associated temperature paths) or tipping points are triggered. C_LIO_LIThe application of damages used within the current study is limited in terms of scope, with damages due to human health impacts and changes in tourism trends missing. In addition to the limited scope, some damages that have been implemented have not been fully allocated to all affected sectors. For example, sea level rise is understood entirely within the purview of loss of arable land while physical capital depreciation and impacts to manufacturing hubs located on coastal areas is not currently simulated. C_LIO_LISociopolitical consequences of climate change such as armed conflict and forced migration are not included. Diminished social resilience due to climate change related impacts (e.g., rising food insecurity) has the potential to feed back into the economy in myriad ways, potentially cascading into additional economic damages and/or altered trade patterns. C_LI C_LIO_LIAlthough limited climate change damages have been implemented, large changes in socioeconomic trends including economic and demographic growth are anticipated to occur within the long-term time horizon used within the current study. Such changes affect key Australian trade partners and have the potential to alter the composition of imports at a magnitude equal to or surpassing climate change impacts. Full simulation of both socioeconomic pathways as well as climate change impacts is currently a CEBRA priority. C_LI 2.2. Changes in pest propagule pressure & establishment exposure hitting Australia.While this report focuses on long-term trends in annual propagule pressure and establishment exposure hitting Australias border, the model is capable of estimating such trends for all 70 global regions and can be readily updated with new interception data. As such, to facilitate interrogation of model outputs, we have developed leaflet interactive maps for each of the five threats. Included in these maps are information4 about temporal trends in pest pressure, establishment exposure (if threat is influenced by climate suitability) and proportion of risk attributable to each infected exporters and commodity sector. The following summarise the key findings we found by running the model for the five exemplar threats: O_LIOut of the five exemplar threats, brown marmorated stink bug (BMSB; Halyomorpha halys) posed the greatest propagule pressure and established risk to Australia. This was followed by giant African snail (Lissachatina fulica), Khapra beetle (Trogoderma granarium), Asian honey bee (Apis cerana), and then spongy moth (Lymantria dispar). C_LIO_LIImports of manufacturing commodities (e.g. electronic equipment, motor vehicles and parts, plastics and metals) from infected countries posed the greatest risk of hitch-hiker contamination, with some exporting regions posing greater risk than others. C_LIO_LIWe detected marginal (albeit uncertain) positive impacts of potential area of suitable climate on the contamination rates coming from infected exporting regions for BMSB and to a lesser extent Spongy moth. This meant that in exporting regions where climate suitability is predicted to increase (e.g. Canada & United Kingdom for BMSB), contamination rates will be higher. By contrast, in regions where climate suitability is expected to decrease (e.g. Italy for BMSB), contamination rates are expected to decline. Area of suitable climate had no discernable impacts on contamination rates associated with Asian honey bee or giant African snail.5 C_LIO_LIDifferences in trends in predicted propagule pressure (i.e. number of contaminated lines) hitting Australias border between the two climate scenarios were found to be small and highly uncertain for all threats examined in this report. Multiple reasons are attributable to this: O_LIThere are compensatory effects occurring, whereby reductions (due to either decreased trade or climate-induced declines in contamination likelihoods) in contaminated items from one infected exporter is made up by increases in another. C_LIO_LIClimate impacts on exports and imports of manufactured goods - the commodity types with highest likelihoods of containing most of the modelled hitch-hikers used in this study - are likely to be severely underestimated. Recent work (Romanello et al., 2023) suggests that the existing set of damages included may severely underestimate the true impacts of climate change, especially on manufacturing sectors. Extending the trade model to include a larger set of damage functions, particularly those that encompass physical capital depreciation due to sea level rise and other disasters magnified by climate change (e.g., bushfires), is expected to result in significantly greater economic impacts within affected manufacturing and related sectors. This in turn will manifest in more significant impacts on global export and import flows, and thus, the total pest pressure expected at Australias border. C_LIO_LIThere remains significant uncertainty on how climate suitability in exporting regions impacts contamination rates. While our model detected marginal positive relationships between contamination rates and area of suitable climate for some threats (e.g. BMSB), uncertainty is partly driven by the number of infected exporting countries containing the threat and how variable climate suitability is within and among those trading partners. This uncertainty could be further reduced by including additional interception data from other countries (e.g. New Zealand) as well as incorporating additional information on other factors likely to impact contamination likelihoods such as known extent of established populations, time since establishment, or other factors that can inform population size in exporting country. C_LI C_LIO_LITrends in Australias exposure to potential BMSB or Spongy moth establishment were expected to decline overtime due to a combination of reduced propagule pressure (caused by declines in volume of trade from high risk trading partners and/or climate-induced declines contamination rates), and declines in climatic suitability at Australian locations where goods are likely to be unpacked. These declines were most pronounced under the worst-case climate scenario (RCP 8.5). By contrast, no discernable trends were found for Asian honey bee or giant African snail - mostly due to 1) minor impacts on trade volumes from infected exporters; 2) negligible impacts of climate suitability on contamination rates; and 3) climate suitability in locations import goods are most likely to be unpacked remaining relatively stable (i.e. where urban centres are predicted to remain). C_LI 2.3. Potential model utilityWe believe that this new model provides the necessary information needed for governments and industry to better anticipate - and therefore manage and adapt to - future climate change impacts on domestic and international economies, global trade, and exposure to biosecurity risk. The current work may serve as a foundation for informing policy decisions as well as a range of downstream models. For example model outputs can be used: O_LIto directly inform both short-term and long-term policies associated with border screening effort among different commodities and exporters, threat prioritisation and developing or updating Import Risk Assessments (IRAs). C_LIO_LIas inputs into other models used by DAFF such as: the post-border pest establishment likelihood model edmaps (Camac et al., 2020, 2021b)6 for informing post-border surveillance & establishment potential, the Risk Return Resource Allocation (RRRA) model, and CEBRAs value model (Dodd et al., 2021) for informing potential damages accrued over time by an exotic threat and the benefits of different mitigation strategies. C_LIO_LIto identify regions and economic sectors most susceptible to changing climate, and thus, provide governments with the necessary foresight to plan and adapt to potential impacts. C_LI