Introduction

Trade and tourism are key to the economies of many countries. However, increasing international trade of fruit and vegetables, and increasing tourist travel has led to more frequent incursions of invasive plant pests (Robinson and McNeill 2022). Tephritid fruit flies are one of the most important invasive and destructive crop pests (Follett et al. 2021). Endemic tephritids cause direct losses, making fruit inedible and adversely impacting the ability to feed a growing world population (Bebber et al. 2014). Additionally, detections of exotic tephritid infestations (eggs, larvae, pupae) trigger regulatory responses to eradicate or contain the incursion (Hancock 2013). Importing countries impose stringent quarantine restrictions to prevent entry of potentially infested fruit or vegetables. Therefore, tephritids have the potential to damage national economies and disrupt both domestic and international trade in fresh fruit.

Mediterranean fruit fly (Medfly), Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) is one of the world’s most serious plant pests (Woods et al. 2005). It is a native of Africa but has spread to many parts of the world. In Australia, it is restricted to Western Australia (Woods et al. 2005; Dominiak and Mapson 2017) but the eastern Australian states are free from Medfly. Additionally, Medfly is not established in New Zealand (MacLellan et al. 2021). Many regions, including New Zealand and eastern Australia, are sensitive to potential incursions of Medfly.

The actual risk posed by Medfly is largely influenced by host species. Hosts can be infested with eggs, larvae or pupae but not all of these life stages become adult flies, even under ideal mass rearing conditions (Fanson et al. 2014). Different hosts are known to have varying capacity to support the tephritid life cycle from egg laying stage to emerged adults. This is measured by the number of adults that emerge from one kilogram of fruit (Cowley et al. 1992) and this metric was termed the Host Reproduction Number (HRN) (Dominiak 2022). The HRN can range from 0 to > 1000 (Dominiak 2022; Follett et al. 2021) placed these HRN into six major categories, based on the log of HRN and these categories were termed the Host Suitability Index (HSI). An additional category is non-host. In Australia, Hancock et al. (2000) listed 53 species as hosts of Medfly, however, there was no ranking based on the HRN to quantify host risk. Here we found data on 146 potential hosts of Medfly and placed these hosts in the order of reproductive capacity (HRN).

Materials and methods

We followed the methodology described by Dominiak (2022). In summary, Google Scholar was used as a search engine because it yields more results than other databases (Pozsgai et al. 2021). The main research term used was “Ceratitis capitata”. Additional terms were added, such as “host” or “suitability” or “susceptibility” or “fruit” and similar terms in successive searches. We examined the results and we chose references if they provided useful data for HRN. Usually, useful references were contained in the first four pages of each search. The third search word was changed, based on the results in earlier searches.

To formulate the table containing hosts, HRN and HSI, we examined each reference for data of each host regarding the reproductive capacity to support adult fruit flies. Where possible, all fruit infestation results are standardized on an individual’s HRN. Most data were based on field sampling. Unfortunately, not all papers reported the information required. Some papers reported infestations per fruit and provided insufficient information to calculate the adults/kg metric. Some papers reported infestation rates in graphs or figures and accurate interpretation was too difficult to obtain reasonable estimates. Other papers reported infestations of larvae or pupae per kg and this information is not reported here. Different papers report a range of HRN figures. In plant biosecurity, the worst-case scenario is always assumed to be the case. Therefore, we did not include any references that reported a HRN lower than the eventual highest HRN in Table 1. Within Table 1, the HRN is followed by the equivalent index (HSI) proposed by Follett et al. (2021).

Table 1 List of hosts of Mediterranean fruit fly showing Host Reproduction Number (HRN), Host Suitability Index (HSI) and the source paper
Full size table

We examined the published literature covering the HRN for Medfly and ranked host plants in descending order based on published HRN (Table 1). Additionally, we assigned each host into one of the potential six HSI categories: HRN = 0 is non host (NH); HRN = < 0.1 is very poor (VP); HRN = 0.1-1.0 is poor (P); HRN = 1.1–10.0 is moderately good (MG); HRN = 10.1–100 is good (G); and HRN = > 100 is very good (VG) (Follett et al. 2021). In our review, numbers of HRN > 20 were rounded out to the closest whole number. Numbers < 20 were converted to one decimal point. We chose the higher HRN where different numbers were reported for a particular host, reflecting the worst-case scenario for biosecurity regulation considerations. There is a broad range within G and VG and there was merit in subdividing these two categories into high and low (Follett pers. comm.), based around the midpoint of the category. Therefore, we added H or L to the G and VG hosts in Table 1.

Africa is the ancestral home of Medfly and data primarily came from Copeland et al. (2002). This was supplemented mainly by Grove et al. (2017; 2019). Liquido et al. (1990) was the primary source for Medfly hosts in Hawaii. Woods et al. (2005) was the source for Medfly hosts in Australia.

Results

We found HRN for 146 potential hosts of Medfly (Table 1). Of these, there were 40 host plants were in the “very good” category (seven hosts were categorised as “very good-high” (VG-H) (HRN > 500) and 33 hosts as “very good-low” (VG-L) (HRN between 100 and 500). We found 61 hosts as “good” (15 good-high (G-H) and 46 good-low (G-L)). Additionally, we found 34 hosts were “moderately good” host plants (MG), five as “poor” (P), zero host plants as Follett’s “very poor” and six host plants were categorised as non-hosts (NH) based on the available data.

Discussion

Two previous reviews were regionally based and examined many tephritids in the Pacific (Follett et al. 2021) and Africa (Dominiak 2022). Our review appears to be the first to propose using HRN on a particular species (Medfly) with the potential to inform a range of management options. Tephritid movements occur through long distance jumps followed by local diffusion (Sadler et al. 2011; Florec et al. 2013) found that it was economically better to invest in better exclusion techniques than enhanced surveillance or enhanced eradication capacity. Hence, importers can use HRN to identify higher risk importations and prepare better risk mitigation strategies to minimise or eliminate incursions of Medfly. However, incursions may still occur. Therefore, surveillance programs could consider HRN to identify the more ideal hosts in which to hang traps. Additionally, exotic incursions are more likely to establish quickly in hosts with a high HRN such as papaya (Carica papaya) with a HRN = 650. These hosts should be targeted with control measures to optimise eradication success. Therefore, if VG and G feral host fruit were removed or treated, pest populations are likely to decline quickly and the emergency response will have a shorter duration, decreasing the cost of the eradication program (Hancock 2013).

This targeting of host fruit based on HRN is particularly important in countries such as New Zealand which has no tephritids (MacLellan et al. 2021). It may be less important where exotic incursions have to compete with established tephritids with higher HRNs in those same hosts (Copeland et al. 2006; Dominiak and Mapson 2017).

We found 40 VG hosts capable of supporting > 100 adults per kg of fruit. Within this group, papaya, Pacific almond, mango, coffee and guava were major hosts. Good hosts was the largest category (41.7%) with 61 hosts. Surveillance and incursion managers should be aware of these species to optimise surveillance or eradication activities. Additionally, the use of HRN to inform and triage surveillance targets should consider factors such as typical size (kg) of fruit. Also, it is unclear whether the HRN translates to the attractiveness of the fruit and preferential selection by Medfly.

The seven hosts with the highest HRN (HRN = VG-H) would be preferred hosts for surveillance including bird plum, bush plum, mock orange, corky passion vine, Jerusalem cherry and Pacific almond (Table 1). However, any host with a HRN > 100 would be ideal hosts for surveillance (40 hosts). In any incursion, these hosts should be fruit stripped to prevent any further rapid Medfly population development. For domestic and international trade, the HRN could be used to vary disinfestation protocols, particularly in a Systems Approach (Dominiak 2019). For instance, should limes (HRN = 0.6) be required to undergo the same treatment as papaya (HRN = 650) where the risk is about 1000 times greater. Additionally, the temperature mediated disinfestation period might be shortened for low HRN commodities to achieve the same biosecurity outcome (e.g. - a given probit level in a Systems Approach). Shorter treatment times would result in a lower carbon footprint of commodities and minimise the impact on global climate change.

In Australia, Hancock et al. (2000) listed 53 potential hosts of Medfly, but there was virtually no ranking of HRN. Based on our review (see Table 1 for details), ten of these hosts were VG hosts, seven were G hosts, 12 were MG hosts and one was a NH. Many authors report hosts of Medfly but not all record the HRN metric: many authors report adults per fruit with no reference to weight of individual fruit. The HRN metric needs to be included in future reports if trade, surveillance and eradication programs are to be optimised. Additionally, knowledge of high HRN hosts would inform eradication managers to rapidly reduce endemic Medfly populations.

It is important to reflect that this host list is not exhaustive. There are many hosts of Medfly referenced in literature that have not been included in this review due to unavailability of data to quantify reproductive capacity. Also, it is important to acknowledge that even though the data suggests that some are potential NH hosts, these hosts need to be considered carefully. For example, feijoa is commonly considered a Medfly host (Argov and Gazit 2008) but we could not find HRN data for feijoa in Africa. Therefore, NH should not be ruled out as a host based on the presented data alone. It is known that factors such as climate, altitude, competition with other fruit fly species and time of year of sampling can influence number of flies found and may account for some NH results.

Here, we have reported the worst-case HRN however these number may not apply to all circumstances. Medfly are found in abundance at lowland and high elevation sites (> 2,100 m ASL) however Medfly were seldom found in lowland areas after the introduction of Bactrocera dorsalis (Hendel) (Copeland et al. 2002). Medfly has a high tolerance of dry conditions compared to B. dorsalis (Hassani et al. 2016) and is capable of withstanding low temperatures (Badii et al. 2015). Therefore, the HRN may be lower than our reported figures based on the local environment, particularly at the margins of its range. Conversely, the HRN may be higher in ideal environmental situations. We encourage all fruit fly researchers to report, where possible, the HRN for all tephritids so that management and trade can be optimised. For example, commercial consignments of papaya, egg plant, apricot, mango and peach needs to be treated before export because of their high HRN. Conversely, based on our findings, low HRN commodities such as feijoa, finger lime, star fruit, pear and banana may require minimum disinfestation before export. Alternatively, these commodities would be suitable for a Systems Approach to production and not require any disinfestation due to their low HRN (Dominiak 2019).