Invasion by non-native species is one of the major threats to the conservation of biodiversity and to the provision of ecosystem services by protected areas. Invasive species often co-occur in protected areas, represented by sparse, isolated individuals or populations in different stages in the process of invasion. Species invasiveness, habitat invasibility and impact also differ between ecosystems, so the risk of invasion varies. Besides, prioritization is required due to constraints on time, financial and other resources. Priority-setting is therefore key to help protected area managers invest efforts on biological invasions that offer the best chances of producing large-scale positive results at the lowest cost possible. A priority-setting scheme for the control of invasive non-native species in natural areas is presented in this paper. The scheme, based on field observations of species occurrences, was applied to the Itatiaia National Park (Brazil). Priorities are calculated from a combination of three criteria attributed to each occurrence: species risk of invasion considering local ecosystems, invasion stage, and species frequency. Data collected in the field in the Itatiaia National Park were used to calculate priorities for 50 non-native species (six animals and 44 plants) in four locations in the Park. The highest priorities were attributed to species of high risk in an early stage of invasion occurring in one site, whereas a few widespread species of low risk were given lower priority. The scheme has proven functional for setting priorities for the control of non-native species in the Itatiaia National Park and in many other protected areas in Brazil.

Invasion risk, invasive alien species, invasive species control, invasive species management, Itatiaia National Park, prioritization framework, priority-setting scheme, protected areas

Invasion by non-native species is one of the major threats to the conservation of biodiversity and to the provision of ecosystem services by protected areas (Foxcroft et al. 2013; Hulme 2018; IPBES 2019). Although the quantification of impacts of invasive species focused on protected areas is still poor in most places (Hulme et al. 2014; Hulme 2018), studies have reported impacts ranging from predation and displacement of native species to changes in community structure and composition, as well as on disturbance regimes and ecosystem functioning (Turner et al. 1997; Loope et al. 2013; Ballari et al. 2015; Lessa et al. 2016; Schmidt et al. 2020).

The importance of protected areas in providing refugia for native species might be even more prominent under climate change (Gallardo et al. 2017). Thus, the control and eradication of invasive species in protected areas must be incorporated as a fundamental component of protected area management. In fact, international agreements and national regulations acknowledge the importance of this issue in different countries. For instance, targets are established in international agreements such as the Convention on Biological Diversity. National regulations, such as the Law 9985/2000 in Brazil, prohibit the introduction of non-native species in certain protected areas and define protected areas as priorities for invasive species control (Dechoum et al. 2018).

Invasive species often co-occur in protected areas, represented by sparse, isolated individuals or populations in different stages in the process of invasion (McGeoch and Latombe 2016). Species invasiveness, habitat invasibility and impact also differ between ecosystems, so the risk of invasion varies. At the same time, the opportunities to effectively eradicate or control invasive species are limited due to constraints on time, financial and other resources, lost opportunity costs and conflicting priorities (Robertson et al. 2003; Cheney et al. 2018). Therefore, priority-setting is key to help natural area managers invest efforts on biological invasions that offer the best chances of producing large scale positive results at the lowest cost possible (Gallardo and Aldridge 2013). A prioritization scheme is any structured system that produces a ranking or ordered set of risk categories (McGeoch et al. 2016). An effective priority-setting system should produce a list of priorities that enables managers to cover more area in less time to manage the best eradication or effective control opportunities first. This has been shown to be more efficient as a management strategy because small invasions have a higher potential to spread than large invasions that have been established longer (Moody and Mack 1988; Emry et al. 2011). This approach is also preventative, especially when addressing populations that are somehow contained, and considers the relevance of early detection and rapid response strategies (National Research Council 2002; Reaser et al. 2020) to avoid future impacts. Individuals that are isolated, especially before reaching reproductive age, are therefore the highest priority especially in relation to those requiring long-term control (Moody and Mack 1988; Hoffmann et al. 2016). This approach also tends to translate into best cost-efficiency.

Priority-setting requires an appropriate evidence base for the definition of control and/or eradication targets (Gallardo and Aldridge 2013). In protected areas, a local assessment of invasive non-native species occurrences and invasion stage is essential for establishing management priorities, considering a preventative approach for the control of individuals or populations, and for actions aimed at eradication. Several prioritization methods have been used in other contexts to date. For example, Robertson et al. (2003) developed a scheme that used a multi-assessor approach for questions that resemble risk assessments. This scheme was used to define priorities based on species. Nel et al. (2004) derived lists of priority species for South Africa using available quantitative data on species distribution and expert knowledge. Later schemes, such as Forsyth et al. (2012) prioritized species first, then combined spatial data with stakeholder input to identify priority catchments for control in South Africa. Cheney et al. (2018) showed that systematic surveys are the best option to generate reliable data for priority-setting schemes, although the cost may be high. Available schemes such as these were however considered too complex for application by managers or field practitioners, too costly, or too time-consuming. In addition, while the majority of existing schemes focus solely on species, the scheme presented here focuses on species, populations and sites with the aim of identifying the best control opportunities of high-risk species, as in the reasoning of early detection and rapid response, and listing the remaining invasions in order of priority.

In this paper, we describe a priority-setting framework for the control of invasive non-native species in natural areas that essentially includes the knowledge of managers. This priority-setting scheme was initially developed in 2007 by the Horus Institute for Environmental Conservation and Development for application in protected areas in the state of Espírito Santo, in southeastern Brazil, and has never been published in the scientific literature. Priorities were defined for occurrences of invasive species in order to optimize control work and the use of financial resources. The scheme has since been used over the last 13 years to develop invasive plant species management plans for approximately 20 protected areas in Brazil. Managers receive training during the development of the plans and technical support to begin practical management. The resulting prioritization is adjusted for each protected area based on the knowledge of managers on local conditions, accessibility, costs, and the existence of susceptible or sensitive sites where control is urgent. A case study applied in the Itatiaia National Park (Brazil) using systematic sampling techniques for plants and mammals is included in this paper.

Four non-native mammal species were recorded in the Itatiaia NP after a total of 298 camera trap*day: domestic cattle (Bos taurus, n = 97), wild boar (Sus scrofa, n = 72), domestic dog (Canis lupus familiaris, n = 10), and European hare (Lepus europaeus, n = 1). Domestic cattle and wild boar were observed in six of the 15 sampling areas, domestic dogs in four, and European hare in one. Three species were observed in Serra Negra (C. lupus familiaris, S. scrofa, and L. europaeus) and three in the highland (C. lupus familiaris, S. scrofa, and B. taurus). No records of non-native mammals were obtained in Santa Clara or in the lowland. Invasion stage (S) was determined as casual for B. taurus and C. lupus familiaris in the highland, and for C. lupus familiaris and L. europaeus in Serra Negra. The invasion stage of Sus scrofa was determined as invasive in the highland and in Serra Negra. In terms of frequency, L. europaeus was observed in one point in Serra Negra, C. lupus familiaris in a few points in the highland and in Serra Negra, S. scrofa in many points in the highland and in Serra Negra, and B. taurus in many points in the highland. Based on the history of invasion of these species and considering the ecosystems in the Park, risk was rated low for B. taurus, moderate for L. europaeus and high for C. lupus familiaris and S. scrofa. Priorities were calculated based on risk, abundance, and spread, resulting in assignment of level 2 for C. lupus familiaris in both Serra Negra and the highland, level 2 for L. europaeus in Serra Negra and level 5 for B. taurus in the highland and S. scrofa in both Serra Negra and the highland (Table 1). The invasion risk factor can be considered as the most important factor to separate species/populations that have the same priority score. As such, because B. taurus does not have a significant history of invasion, the final adjustment on the scheme would place it as the last population to be managed unless other evidence indicated the need for urgent action.

A total of 36 non-native plant species were registered at the sampling points along roads and trails (Table 2). Of the 12 plant species in the highland, three species occurred only in casual populations, one in naturalized populations, and eight in invasive populations. In the lowland we registered 25 non-native species: 14 species in only casual populations, seven naturalized, and four invasive. In Santa Clara we registered seven non-native plant species: three species in casual populations, two naturalized, and two invasive. In Serra Negra we registered three non-native plant species: one species in casual populations and two in invasive populations (Table 2).

Invasion risk was considered low for 17 of the 36 species, while ten were rated moderately invasive and nine highly invasive (Table 2). None of the non-native plants registered in our survey occurred both in the highland and in Serra Negra, whereas only one species was recorded both in the highland and lowland, or in the highland and in Santa Clara. In total, four species were assigned priority level 1, three species level 2, fourteen species level 3, five species level 4, six species level 5, seven species level 6 and five species level 7 (Table 2). The lowland was the area with the highest number of species in priority level 1 (C. dactylon, I. walleriana and M. maximus), and the highland was the area with the highest number of low priority species (category 7: A. odoratum, P. vulgaris and T. repens). The four species in priority level 1 only occur in casual populations in one location, but are species of high invasion risk in the ecosystems considered. On the other hand, the five species categorized as level 7 are species with populations widespread due to cattle farming prior to the establishment of the Park, but these are ruderal species of low risk without significant history of invasion (Table 2).

Details on the usability and application of a simple priority-setting scheme are described in this paper to support the management of invasive non-native species in protected areas. As per the prioritization scheme, the highest priorities for control were attributed to species of high invasion risk in early stages of invasion restricted to one location (e.g. C. dactylon and C. familiaris in this case study), whereas widespread species of low risk were given lower priority (e.g. C. asiatica and B. taurus in this case study).

Among the three criteria used in the priority-setting scheme, classifying species risk, interpreted as the propensity of a species to invade the local ecosystems, may be the most challenging part given the general lack of training of natural area managers and other field practitioners on invasive non-native species, or knowledge of species and their behavior in local conditions. In these cases, invasive species databases (e.g. the Horus Institute in Brazil, CABI ISC and ISSG GISD) as well as the EICAT scheme (Environmental Impact Classification for Alien Taxa) (Hawkins et al. 2015; Evans et al. 2016), or available results of risk assessments (e.g., online sources, da Rosa et al. 2018; Ziller et al. 2018) can be used in addition to field observations to support decisions on the level of risk of each species. The disadvantage of using generic information is that although there may be records of invasion, impact, or results of high risk from assessments that refer to other parts of the world, the information may not apply well to local ecosystems. Additionally, present and future climate and habitat types should be considered when using these alternatives whenever possible, and especially, expert opinion and field observations. Quantitative risk assessments are often underused because they tend to be time-demanding or require data that is not readily available (McGeoch et al. 2016).

Although the scheme proved useful to define priorities for control in the Itatiaia NP, knowledge of invasive species and their potential or current behavior in the ecosystems considered is important for its application. For instance, in our case study, the inclusion of species such as Hydrangea macrophylla, Bidens pilosa, and Quercus robur, which are in turn cultivated (H. macrophylla) and ruderal, as well as species that require long-term, persistent control and have expanded beyond small and few patches, such as African grasses, pushed aggressive invasive species such as Hedychium coronarium and Tradescantia zebrina down the list because these have invaded larger areas in the Park. Species that are characterized as not invasive or ruderal, such as the ones mentioned above (H. macrophylla, B. pilosa, and Q. robur), should be placed in a separate table to ensure that all species with a history of invasion are treated first. An initial effort in separating species with and without invasive potential will help managers filter the most important populations and species for control. This information cannot be obtained from general data sources, as it refers to the local ecosystems under consideration, and requires expert opinion as well as field observations. For this reason, species referenced in global databases as ruderal or invasive only in agricultural areas should be considered of low risk unless invasive behavior is actually observed locally, or other evidence corroborates higher risk.

In this study, formal sampling techniques were applied for data collection on non-native species. Although systematic sampling will produce the best possible data set (Cheney et al. 2018), this is, however, not the only approach for data collection. With training and experience, protected area staff can conduct field surveys to register the occurrence of non-native species with a GPS, while noting down invasion stage and frequency, as well as inferring invasion risk. Furthermore, information can be obtained from published sources. Effective prioritization must consider not only invasive species and pathways, but also the sites most sensitive and susceptible to invasion (McGeoch et al. 2016). This information can only be obtained locally, therefore invasion patterns must be observed during the surveys and used in the attribution of invasion risk. Information from other references is useful to corroborate these assumptions, as mentioned before. Cheney et al. (2018) demonstrated how mistaken general perceptions can be, as there was substantive disagreement between datasets produced by managers and by systematic sampling, implying that field data has to be collected locally. The application of our scheme entails full cover of protected areas, or of entire sections in the case of former prioritization of sites for control, very large areas, or very limited financial resources. Input from protected area managers is key especially after an initial list of priorities is defined based on field surveys. Logistics, as well as potential impact on fragile areas or on areas with threatened or endemic species, are discussed to adjust the operational sequence. At this time, knowledge of the area, accessibility, transportation or walking time, and many other details are considered to adjust the sequence of priority areas and species populations. Still, it is the priority levels that guide implementation. This last phase in the application of the scheme allows for flexibility and incorporation of exceptional circumstances regarding threatened or endemic indigenous species, susceptible or sensitive sites that may justify shifting the order of some priorities.

It is always best to register species occurrences by sectors of a natural area that are well-known by those in charge of management (e.g. entrance, headquarters, bridge, specific trails and other names in use). Once the list of priorities is generated, local managers must decide which sectors should be treated first, for example, due to the presence of threatened native species, unique or fragile habitats combined with other complementary criteria such as accessibility. Resulting workplans will only be useful if taking local experience and knowledge of protected area staff into account, especially to define implementation.

Control efforts should begin by addressing the priorities with the lowest numbers (priorities listed as 0 or 1 first, then 2, and so on up to priority 7). Priority zero indicates the occurrence of a non-native invasive species which might not yet have spread, providing an opportunity for elimination before it invades, but contained species may in certain cases not require management either because they cannot escape or because they are not aggressive. These occurrences should be evaluated on a case-by-case basis. Species of higher risk should be treated first within the same level of priority. The operational sequence of the priority-setting scheme should respect the list of priorities as much as possible, but is flexible to be adjusted to optimize logistics.

Because control requires persistence to prevent species from reproducing in order to reduce existing populations, monitoring and control are part of a continuous cycle once management begins (Fig. 1). This cycle ends either when the invasion is eliminated or due to other reasons such as limited funds or personnel, or others that lead to the interruption of activities. Complementarily, capacity-building for invasive species management is a key component of efficiency in the control of invasive species, especially to avoid wasting time and resources and to avoid missing important opportunities of restoring natural areas or creating negative references.

Most protected areas around the world face the threat of multiple invasive species and managers are required to implement control practices to limit the spread and impact of invasive species. However, resources and time are often limited for controlling all invasions at once (Robertson et al. 2003; Forsyth et al. 2012). Thus, priority-setting is key for the effective management of invasive non-native species (McGeoch et al. 2016). The priority-setting scheme presented in our paper is intended to be simple and functional for prioritizing invasive non-native species for eradication or control. As it has been designed for application by protected area managers or field practitioners, it can be readily implemented in any protected area.

We thank CNPq-Brazil and ICMBio for funding (grant number 421254/2017-3). RADS and HMR thank Capes-Brazil for their Master´s scholarships. RDZ also thank CIB for partially funding his participation in the ‘Frameworks used in Invasion Science’ hosted by the DSI-NRF Centre of Excellence for Invasion Biology in Stellenbosch, South Africa, 11–13 November 2019, which was supported by the National Research Foundation of South Africa and Stellenbosch University.