Christmas Island lies in equatorial waters in the Indian Ocean, 370 km south of Java Indonesia and 1400 km northwest of Australia. The island is a submarine volcanic seamount that has been above the ocean surface for approximately 5 million years (Ali and Aitchison 2020). Total land area is 135 km², most of which is greater than 150 m above sea level (ASL), forming a plateau; the highest point (Murray Hill) is 359 m ASL. The basalt core is mantled by a sequence of Eocene to Quaternary limestones that are often expressed as cliffs, scree slopes, outcrops and pinnacles (Barrie 1967; Grimes 2001). A few different soil types occur on the island, and they are predominantly derived from weathered substrate rocks (e.g. limestones or volcanics) or marine sediments accumulated during submergence phases. The depth of the soil profile is commonly less than 4 m but can range from zero (where limestone outcropping is present), to 80 m where fault or fissure infilling has occurred. Soils are often shallower on the geologically more recent lower terraces than on the central plateau.

The island has a tropical monsoonal climate, with most rainfall occurring between December and April. Long term average rainfall is 2200 mm pa, but this can be highly variable from year to year, ranging from 1067 mm (1987) to 5120 mm (2016) (Bureau of Meteorology 2020). Temperatures are very stable, with minimums of around 20 °C and maximums of around 29 °C. Relative humidity averages around 80%–85%. South-easterly trade winds dominate in the dry season (July to October), and north-westerly winds dominate in the summer wet season (Bureau of Meteorology 2020).

These conditions support a dense tropical rainforest across much of the island, with a canopy typically around 35 m and some emergent trees on the plateau approaching 50 m. The remote, isolated nature of this island has given rise to at least 253 unique species of fauna and flora, with endemic plants accounting for 17, possibly 18 species (Director of National Parks 2014; James et al. 2019). A total of 213 species of native plants has been reported (Claussen 2005). The Flora of Australia (1993) provides the most comprehensive description of vegetation types on the island, including seven old-growth/primary native vegetation types and two categories of secondary vegetation on historically cleared areas. Geoscience Australia (2014) developed a map showing vegetation and clearing patterns based on aerial images and LIDAR data (captured in 2011). A simplified form showing all five primary native vegetation types and historically cleared areas is shown in Fig. 2.

Figure 2.

Main vegetation types and historical clearing boundary on Christmas Island (data courtesy of Geoscience Australia 2014).

Rainforest on Christmas Island is tallest over areas with deep soil (Flora of Australia 1993). In areas where limestone is nearer the surface (on the terraces), tree heights are reduced, the canopy is more open and diversity is often higher (Flora of Australia 1993). Forest on the plateau is evergreen with a closed canopy (>90% foliar cover) throughout the year. Vegetation on the terraced margins of the island is semi-deciduous (including both semi-deciduous forest and semi-deciduous scrub forest) and during long dry periods can become quite open (<50% foliar cover). This increases the invasibility of these forest types (Swarbrick and Hart 2000; Fine 2002; Green et al. 2004). Tree falls are common in all forest types, especially during wet season storms, and can provide opportunities for weed invasion.

The greatest disturbance factor, however, has been mechanised clearing for phosphate mining. Approximately 25% of the island’s rainforest has been cleared for mining and associated developments since the island was settled in the 1880s (Fig. 2). As a quarry-type operation, large areas are cleared to remove the soil profile (~4 m), often leaving behind little or no soil on the pit floor. The post mining landscape is typically characterised by limestone pinnacles that can be deeply incised, sometimes standing over 5 m tall. Once equipment has dug out such areas, it can be impossible or too costly to access them again, meaning they can harbour weeds and be beyond control efforts. Only a small fraction of the total mined area can be rehabilitated sufficiently to restore even basic ecological functionality. Remediation works involve the use of heavy machinery, such as dozers, excavators, loaders and haul trucks, to rip compacted pit floors, break down limestone pinnacles and bring in what little soil is available from backfill stockpiles, generally at great expense. Early attempts at rehabilitation by mining companies in the 1970s involved planting a range of non-native tree species such as Aleurites moluccana, Melia azedarach, Sesbania grandiflora, Syzygium jambos and Spathodea campanulata, many of which have persisted to become weeds (Carew-Reid 1987). Since 1992, rehabilitation efforts have been carried out by the Australian Government’s Christmas Island Minesite to Forest Rehabilitation program, using funds paid by the current mining company as a condition of its lease. New and old areas are being rehabilitated, with around 20,000 native trees planted each year. Weed control is a major component of the program.

Edges between rainforest and cleared areas, such as along roads, former drill lines for mineral exploration, railway lines and around mining pits, are extensive (Swarbrick and Hart 2000). Approximately 63% of the island is national park, 93% of which is old-growth primary forest (7851 ha) and the remainder is mostly rehabilitation fields. In addition, approximately 2337 ha of old-growth, primary forest is currently held on Unallocated Crown Land. Including pockets elsewhere, there is a collective total of ~10,215 ha of old-growth primary vegetation (all naturally occurring vegetation types). These virgin forest areas host the island’s endemic and formally listed threatened species, and therefore are the priority for managing impacts from invasive species and human disturbance.

Panetta (2015) proposed a method for categorising plant species in terms of the species-intrinsic feasibility of eradication, based upon three attributes: 1) the time to reproduction (i.e., duration of the juvenile period); 2) the level of seed persistence; and 3) the potential for long distance dispersal (LDD), which has a disproportionate effect on the rate of spread (Nathan 2006).

In the case of containment feasibility, seed persistence is considered to be of secondary importance because the primary management focus is on the spread of a plant from a site rather than its persistence there (Wilson et al. 2017). The ability to contain a weed will depend therefore upon the potential for controlling its reproductive output, as well as the subsequent dispersal of whatever propagules are produced despite management actions (Panetta and Cacho 2014). Thus, the key determinants of containment feasibility are time to reproduction and the potential for LDD. A proxy for the latter is whether the dispersal suite (sensu Panetta 2012) is dominated by natural dispersal vectors such as wind, water or wild animals, or by humans and their agents. For the Christmas Island weeds under consideration, wind and wild animals (birds and bats) are the most active contributors to LDD (Swarbrick and Hart 2000). Potential reproductive output is another trait that can be considered in the determination of containment feasibility (Fig. 1). However, we do not address it here because a fundamental component of containment is the prevention of reproduction, even though some reproductive escape (Panetta 2007) may occur.

Consistent with the definition of risk assessment as threat (or hazard) × likelihood (Daehler and Virtue 2010), weed risk assessment involves an evaluation of species in terms of both their impact (threat) and their invasiveness (i.e., potential for spread, sensu Richardson et al. 2000). Various flora surveys over the past century, including several conducted during the last few years (by the Australian National Herbarium 2012 and 2019; Department of Agriculture, Water and Environment 2019; and Parks Australia), plus a review by Lohr et al. (2016), have identified more than 600 introduced species on Christmas Island. From this pool of introduced species, the whole-of-island weed risk was assessed for 130 species that had shown evidence of naturalisation. Personnel (n = 10) from Parks Australia, the National Herbarium, the Department of Agriculture, Water and Environment, and private consultants provided input that was compiled by Parks Australia to reach consensus. Many of the factors included in the Australian weed risk assessment model (Pheloung et al. 1999), such as potential adaptation to local conditions, weed history, plant type, undesirable traits, reproduction, dispersal mechanisms and persistence attributes were considered. More than 70 species were deemed problematic for secondary vegetation types, such as rehabilitation plots and other disturbed areas. Given that our focus here relates only to old-growth, primary vegetation types, species whose impact was restricted to secondary vegetation types were removed. This resulted in a pool of 31 priority species (Table 1) that had been assessed as ‘high’, ‘very high’ or ‘extreme’ risk, a ternary categorisation resembling that employed by Booy et al. (2017) to prioritise non-native organisms for eradication.

From these whole-of-island risk assessments, species were scored according to the risk posed to two major plant communities on the island: closed-canopy evergreen rainforest (on the deep soils of the island’s central plateau) and semi-deciduous scrub forest (on the shallow soils of the coastal terraces). Among the natural, primary vegetation communities on the island, these two vegetation types represent the endpoints of a continuum of invasibility, with the former being less invasible than the latter and semi-deciduous forest representing a transition between the two (Swarbrick and Hart 2000). In general, pristine tropical rainforests have a low invasibility for most weeds, and only shade tolerant non-native species pose a threat (Fine 2002) – that is, until a disturbance (natural or anthropogenic) takes place and allows opportunities for invasion by a broader range of weed species. The exclusion of most weeds by tropical rainforests has been attributed to the fact that the great majority of species that are transported to such areas lack specific life history traits, most importantly shade tolerance, necessary for invasion in the absence of disturbance (Fine 2002).

Species designated ‘extreme risk’ were those considered to have the potential to transform (Richardson et al. 2000) at least one of the communities. These species were scored as ‘4’. Those posing a greater risk to one community than the other were designated as ‘very high’ risk (scored as ‘3’) in the former and as ‘high’ risk (scored as ‘2’) in the latter. In some cases, low recruitment, survival and growth had been observed in one of the communities (e.g., Syzygium grande and Hevea brasiliensis in semi-deciduous scrub forest and Tecoma stans, Ipomoea spp. and Macroptilium atropurpureum in the closed evergreen forest). These species were designated ‘other’ risk (scored as ‘1’), such that all lower categories of risk were combined.

Chromolaena odorata (Siam weed) is another species that could potentially transform semi-deciduous forest types. A small, but seed-producing population was discovered in 2010 (Dodd et al. 2012) and was immediately destroyed. Recruits, all of which were controlled, continued to emerge during wet seasons for seven years. Monitoring is continuing – extensive searches for this species by Parks Australia staff have been conducted at least twice per year, but it has not been detected in any other location. While exhaustion of the C. odorata seed bank at the known outbreak site has likely occurred, there remains a possibility that this weed remains undetected elsewhere, or could re-invade the island, most likely from the Cocos Keeling Islands (~970 km away) via sea or air transport. Should C. odorata be detected again on Christmas Island, it would be targeted for eradication so it is not considered further.

We reiterate that numerous species were excluded from the priority list because they are considered less of a threat to intact, virgin forest types, but following significant disturbance would possibly need to be brought back into consideration.

As in the system proposed by Panetta (2015), species were classified according to whether their juvenile periods were less than or equal to 2 years, or more than 2 years (scored as ‘1’ and ‘2’ respectively – the higher score aligned with greater containment feasibility). Species whose potential for LDD is high were scored as ‘1’ and those for which LDD potential is relatively low were scored as ‘2’, again with the higher score aligned with greater containment feasibility. Containment feasibility score totals therefore ranged between 2 and 4 (Table 1). Because our emphasis was on the characteristics of species that contribute to their spread potential, we did not include plant community invasibility in our estimates of weed containment feasibility.

Priorities for containment were obtained for individual communities by combining weed risk assessment ratings with the containment feasibility ratings for each species.

Consideration of the spatial distribution of each species, landscape features, management aspects and social considerations will be required for the more thorough weed risk analytical assessment. Our weed risk analytical screen is a key input to the analytical process (Fig. 6) because it encapsulates the risk posed by each species, as well as its potential for spread. The latter is largely determined by how quickly a species produces propagules, in conjunction with propagule adaptations that increase the likelihood of long distance dispersal.

Figure 6.

Contribution of initial screening to weed risk analysis. Grey shaded elements are addressed in the present treatment. Note that some species may need to be eliminated from consideration owing to social considerations.

In our view the relative importance of these components of weed risk analysis requires further investigation. In prioritising species for eradication Booy et al. (2017) assumed a symmetric relationship, i.e., a species that was evaluated as posing a high risk in conjunction with medium feasibility of management should receive the same priority as one that posed a medium risk and high management feasibility. Taken to the extreme, the acceptance of this relationship means that a low risk species with high management feasibility would be accorded the same priority as a species manifesting the opposite combination, but we question the rationale of allocating scarce resources to the management of any species considered to pose a low risk. We maintain, on the other hand, that risk should have a higher weighting – given resourcing constraints, only the species that pose the highest risk should be considered for coordinated control, with prioritisation within this group informed by management feasibility (as shown in Figs 4 and 5 for weed risk analytical screening). We consider this assertion to have general application, not being restricted to the system under examination. A consequence of lower technical feasibility is that more resources will be required to achieve a given management goal (Panetta 2015; Wilson et al. 2017). In the present context, extreme-risk species may still warrant containment even if projected management costs are high relative to those associated with species posing lower risk. This is a prime example of the application of the precautionary principle in risk management, as advocated recently by Strubbe et al. (2019).

Two fundamental issues must be considered when attempting to set subgoals for a containment program. The first relates to the counterfactual scenario (i.e., the rate of spread that would occur in the absence of intervention) against which the degree of spread reduction could be assessed. The second relates to the value of reducing this baseline spread rate.

Various models have been used to estimate spread rates of different organisms, including non-native plants (Higgins and Richardson 1996; Parry et al. 2013). Each modelling approach has its strengths and weaknesses, but key concerns include scale and complexity, the choice of theoretical versus empirically based models and, particularly relevant to the spread of plants, the existence of multiple dispersal pathways. Estimations of model and parameter uncertainty will be important for the purposes of decision making (Parry et al. 2013). It is likely that any modelled baseline spread for an invasive plant would be accompanied by wide confidence intervals, especially where the potential for long distance dispersal is a critical factor.

As was stated at the outset, slowing spread can provide substantial benefits. Net benefits of containment, which incorporate the costs of containment actions, can be identified through bioeconomics, i.e., the optimal management of renewable biological resources. Bioeconomic models can be used when only rough estimates of benefits and costs are available (Cacho 2006). However, any form of benefit/cost analysis of invasive species management is subject to biases that may lead to underestimation of costs and overestimation of benefits (Dahlsten et al. 1989; Myers et al. 1998) and therefore can be associated with ‘‘extremely wide confidence intervals’’ (Simberloff 2003, p. 251). The net value of a containment program (benefits accrued minus program costs) can be expected to vary with the degree of reduction of spread. The theoretical form of this relationship is a matter for speculation, but it is possibly non-linear, with increasing net benefits per unit spread reduction as absolute containment is approached.

Since the reduction of spread and its value can be expected to have wide confidence limits, it is important to be aware of the risk of false precision (Roberts 2017). In the first instance, the articulation of precise management goals (such as “70% reduction of spread”) should be avoided. In the second, the degree of confidence in a measure such as the unit risk reduction (in terms of damages averted per dollar invested) might not be high, however valid such quantification might be from a theoretical perspective. Rather, given an acceptable estimate of containment feasibility, we suggest the way forward may be to adopt containment as an ‘aspirational’ objective and use measurements of spread over time (Panetta 2012) as a basis for deciding whether to continue a containment program or switch to an alternative strategy, such as asset protection (Auld and Johnson 2014). This is analogous to the approach that is taken with weed eradication, which is also essentially an aspirational goal. If over time an eradication program fails to demonstrate progress, this management goal may be abandoned (Panetta 2015). The goal of absolute containment has a discrete set of potential outcomes (spread is either stopped or it is not). For relative containment, however, a multitude of outcomes would meet the management objective – strictly speaking, any non-zero degree of spread reduction less than absolute containment. The determination of what is an acceptable level of spread reduction is clearly beyond the scope of this paper. As per the argument presented above, the output of any such determination is likely to be a range of values, the breadth of which would be related to levels of uncertainty in the counterfactual scenarios of weed spread rate and impact in the absence of management intervention.

The closed-canopy evergreen rainforest is intrinsically less invasible in the absence of disturbance, but at the same time hosts most of the island’s endemic and formally listed threatened plant species. Clausena excavata is a rare example of a weed that can establish under an intact canopy and should be prioritised for control, whether via a formal containment program or in terms of asset protection. It has proven to be an invasive non-native weed in tropical forests elsewhere around the world (Viera et al. 2010; Roseleine and Suzuki 2012; Biswas and Das 2014). Growing slowly under low light conditions, the species probably depends upon gaps created by tree falls to become reproductive. Seven other species are considered to pose a very high, and 17 species a high risk to the rainforest (Fig. 4).

Tropical cyclones have been relatively uncommon for Christmas Island, with roughly only one significant system impacting the island every decade or so. However, if cyclones become more intense and/or more frequent because of climate change, this could have major implications for the invasibility of the island’s primary vegetation types, including closed-canopy evergreen forest. A cyclone in 2014 (TC Gillian) caused significant damage across the island, stripped much of the forest canopy and gave M. micrantha the opportunity to greatly expand its range into intact forest areas where it had never previously been able to establish. Given that this species has seed that can persist in the seedbank for up to seven years (Brooks et al. 2008; Macanawai et al. 2018), it will likely become more problematic if cyclones occur more frequently. That said, an effective biological control agent, the rust fungus Puccinia spegazzinii (Day and Riding 2019) has now been approved for release on the Australian mainland and may soon be available for use on Christmas Island, pending the outcome of a separate import approval process. When widely established, the rust should reduce the effort required to control M. micrantha by other means. This illustrates the containment benefit of ‘buying time’ until a more sustainable control measure becomes available.

The native forests of Christmas Island have been substantially cleared and fragmented by mining for phosphate minerals. Island ecosystems and island endemic species are notoriously vulnerable to impacts, declines and extinctions because of habitat disturbance and the associated compounding threats of invasive flora and fauna (D’Antonio and Dudley 1994; Lonsdale 1999; Denslow 2003; Gimeno et al. 2006; Vilà et al. 2006; Reaser et al. 2007; Baider and Florens 2011; Andrew et al. 2018; Heger and Andel 2019; Brock and Daehler 2020). In addition to more than 3,000 hectares of broad-scale clearing, approximately 500 km of mineral exploration drill lines have also been made in a systematic grid pattern across much of the island, predominantly through the closed-canopy evergreen forest on the plateau (Parks Australia 2009). Most of these drill lines were pushed through in the 1950s, 60s and 70s, before many of the weed species of current concern were widely distributed on the island. In the relative absence of problem weeds, drill lines once naturally regenerated by successional processes involving native species. The vegetation on old drill lines is often almost indistinguishable from primary forest. From an ecological perspective it has regained full ecosystem functionality, with mature trees offering bird nesting opportunities and an abundance of red crab burrows. The expansion of numerous weed species across the island in recent decades has significantly altered the ecological dynamics of colonisation and succession. Aggressive invaders such as C. excavata, M. micrantha, L. leucocephala and others now overgrow and out-compete native recruits and have been observed colonising recent drill lines and cleared areas. There are now many weeds that will colonise and dominate larger disturbed areas (Fig. 4). Furthermore, newly formed edges to intact vegetation enable weeds – especially the more shade tolerant species such as C. excavata – to encroach into primary vegetation. Left unchecked, there is little doubt that weeds will dominate post clearing recruitment, cause major edge effects and progressively invade forest types on the island. This highlights the critical importance of minimising further forest fragmentation via all forms of anthropogenic disturbance as part of a holistic approach to weed risk management.

Decisions concerning which weeds of natural ecosystems are targeted for control, as well as the type of control that is to be undertaken, need to be based on the degree of risk posed and the degree of difficulty that can be anticipated in attempting to manage it. Prioritisations of species for control need to be framed with reference to individual plant communities, since weed risk can be expected to vary according to the environmental context. Stringent limitations in the availability of resources for management generally imply that only the species that pose the highest levels of risk should be considered for co-ordinated control. We have shown that traits that contribute to the species-intrinsic feasibility of eradication may also be useful in assessing the feasibility of containment for species with restricted distributions, thereby assisting in the prioritisation of weeds to this management end. The development of a method for considering the spatial distribution of each species, landscape features, management aspects and social considerations is underway.