ARTICLE IN PRESS Journal for Nature Conservation 12 (2004) 171—179
www.elsevier.de/jnc
Assessing the risk of potentially invasive plant species in central Europe Ewald Weber, Daniel Gut Swiss Federal Research Station of Fruit-Growing, Viticulture and Horticulture, CH-8820 Wa ¨denswil, Switzerland Received 10 September 2003; accepted 30 April 2004
KEYWORDS Biological invasions; Environmental weeds; Invasiveness; Prediction; Risk assessment
Summary A risk assessment system was developed to assess the invasion potential of new environmental weeds in central Europe. A pre-evaluation step excludes species that are officially controlled, widespread, or intended for use in protected cultures only. Species eligible for risk assessment are classified into three categories (high risk, further observation required, low risk) by rating them according to various biogeographical and ecological aspects. The rating system was validated by testing 47 well-known invasive plant species of temperate Europe and 193 exotic plants which have failed to establish themselves in Switzerland. The overall accuracy was 65%. Accuracy of correctly predicting invasive species was 77%, while accuracy of correctly predicting non-invasive species was 62%. The proposed risk assessment protocol should be understood as a first attempt for a European country and needs modifications. These can only be achieved by applying the system in practice. & 2004 Elsevier GmbH. All rights reserved.
Introduction The spread of exotic species into natural communities is threatening native biological diversity and the functioning of ecosystems, and is occurring at an alarming rate (Pimentel, Lach, Zuniga, & Morrison, 2000; Sandlund, Schei, & Viken, 1999; Weber, 2003). The significance of invasive species as a global environmental problem is widely
recognised, and article 8(h) of the Biodiversity Convention asks for measures ‘‘to prevent the introduction of, control or eradicate those alien species which threaten ecosystems, habitats or species’’. As more and more exotic (alien, nonnative) plant species are introduced and become naturalised in most regions of the world, the likelihood of new invasion events with subsequent negative ecological impacts on the native
Corresponding author. Geobotanisches Institut, Swiss Federal Institute of Technology, Zu ¨richbergstrasse 38, CH-8044 Zu ¨rich,
Switzerland. Tel.: +41-1-632-7457; fax: +41-1-632-1215. E-mail address:
[email protected] (E. Weber). 1617-1381/$ - see front matter & 2004 Elsevier GmbH. All rights reserved. doi:10.1016/j.jnc.2004.04.002
ARTICLE IN PRESS 172 communities increases rapidly (Vitousek, D’Antonio, Loope, Rejma ´nek, & Westbrooks, 1997). Thus, in addition to already existing invasive species, managers of protected areas and wildlife refuges are increasingly facing the need to handle new plant invasions. They also do not know how to react to newly appearing exotic species for which invasion potential is unknown. To prevent new plant invasions, there is an urgent need for the development of early warning systems to determine the likelihood of a given species becoming invasive and of methods to conduct rapid assessments of the status of invaders (Panetta & Scanlan, 1995; Sandlund et al., 1999; Groves, Panetta, & Virtue, 2001; Wittenberg & Cock, 2001; Andow, 2003). Preventive measures would ideally consist of the prevention of entry of a species, and the restriction of spread once the species is present (Zamora, Thill, & Eplee, 1989; Westbrooks, 1991). Both require knowledge on the invasive characteristics of the species under consideration. Most of the invasive weeds of a region were originally introduced intentionally for economic and other purposes and now their control incurs high expenses (Pimentel et al., 2000). For example, more than 70% of the naturalised exotic plants in Australia had been introduced as ornamentals or for agricultural purposes (Nairn, Allen, Inglis, & Tanner, 1996). These examples illustrate that it is possible to avoid damage to native ecosystems by exotic species and the associated costs if such harmful species are not used and planted in the first place. However, this step requires knowledge as to whether a particular species will become invasive where it has been introduced but is not yet widespread, or where it is intended for introduction, e.g., the species must be recognised as potentially invasive. Although prediction of invasiveness in plants is far from being obvious, especially because of the absence of key characters, several attempts have been made to assess the likelihood of invasion. Richardson, Cowling, and Le Maitre (1990) defined functional groups based on life-history traits important for invasion in a fireprone area, in order to assess invasive potential in different species of Pinus. Five functional groups could be distinguished, representing groups of different invasion success. Taxa in the group of highly invasive pines had small and wind dispersed seeds, a short juvenile period, and fire-resilience. Scott & Panetta (1993) developed a method of predicting weed status for plants with southern African origin naturalised in Australia, using data on distribution, taxonomy and weed status outside Australia. Variables with a high predictive value
E. Weber, D. Gut were weed status, climatic range in the home country, and the existence of congeneric weeds in the home country. In order to produce a tool to screen new introductions of woody plants for invasion potential, Reichard & Hamilton (1997) developed a decision tree that allows in a simple way to allocate species into three classes (high risk, low risk, further investigation required). The United States Department of Agriculture (USDA) uses a weed risk assessment protocol to regulate species introductions and to prevent new weed problems (Lehtonen, 1998). A similar scheme is implemented in weed management in Australia (Pheloung, 1996). Hiebert & Stubbendieck (1993) developed a decision-making tool for prioritising control efforts against exotic plant species by ranking them according to their ecology, spread potential, costs, and impacts on the native communities. Tucker & Richardson (1995) developed an expert system for recognising woody plants potentially invading South African fynbos. In the case of animals, Smallwood & Salmon (1992) developed a simple rating system to assess the invasion potential of birds and mammals. These examples illustrate that although ecological theory has not yet achieved predictive models, it is possible to recognise potential harmful species to at least some extent. In fact, sound models that could be applied to predict invasiveness are needed urgently, including quick and easy-to-perform assessment protocols to screen exotic plant species for their potential invasiveness. Such tools can be of great help in prohibiting the use of potential invasive species for example in horticulture and landscape architecture, in regulating the plant trade, and to set priorities in managing newly appearing exotic species in protected areas. In central Europe, a risk assessment system for the impacts caused by invasive plant species does not yet exist, although an ongoing discussion in Germany on how to deal with invasive plant species emphasises the necessity of such protocols (Doyle, 1999). The European Plant Protection Organisation (EPPO) has, however, developed a pest risk assessment scheme that covers any pest organisms including plants (http://www.eppo.org). In this paper, we present a rating system to assess the invasion potential of exotic plant species in a central European country. We designed the rating system to meet the specific needs for central Europe and focused on plant species that may become invasive in this region. We then validated the rating system by applying it to exotic plant species of Europe that had variable degrees of success in becoming established.
ARTICLE IN PRESS Risk assessment system for invasive plants
173
Methods Risk assessment protocol Existing protocols available from the literature (Panetta, 1993; Hiebert & Stubbendieck, 1993; Scott & Panetta, 1993; Pheloung, 1996; Reichard & Hamilton, 1997) were modified according to the specific demands of an European country. We chose a ranking system because it is simple and most appropriate for the purpose here. It was our aim to set up a system that is widely applicable and suitable for any species, and one that relies on easily available data. The procedure begins with a pre-evaluation step (Fig. 1), in accordance with pest regulation standards of the European Plant Protection Organisation (EPPO). The pre-evaluation step excludes those species that are not justified for risk assessment; e.g., species that are already widespread, under official control or listed as a quarantine species, or unlikely to become natur-
Does the species occur in the risk area?
Confirm species idendity
START
alised for obvious reasons. Such a step is necessary in order to ensure that the introduction of species with considerable economic benefits is not prevented. Plant species considered suitable for risk assessment include any exotic species that is not yet present, has a restricted distribution in the risk area, and is planned to be introduced and commercially used on a large scale. The rating system (Appendix A) allocates scores to the species for biogeographical, ecological, and experience-linked aspects. The scores of the 12 questions are summed up, and species are classified into ‘‘high risk’’, ‘‘intermediate risk’’, and ‘‘low risk’’.
Source of data The necessary data for the species were obtained from various sources. Status of the species as a weed elsewhere was taken from Holm, Pancho, Herberger, and Plucknett (1979) and Anonymous (1992). Geographical distribution data for Europe
NO
YES
NO
Is the species officially controlled or a quarantine species?
NO
Is the species being introduced intentionally for a special purpose?
NO
YES
Is the species widely distributed in the risk area?
Is the species planned to be grown only inside?
YES
Is there any evidence that an accidental introduction is unlikely?
NO
YES
YES
Stop
NO
YES Stop Did the species arrive recently?
NO
Will the species be grown on a large scale?
Stop
NO
YES YES
Evaluate risk
Is the species solely a weed of agricultural areas?
NO
Evaluate risk
YES
Stop
Figure 1. Pre-evaluation of plant species for the risk assessment scheme (see Appendix A). The purpose of the preevaluation is to exclude those species that do not qualify for being assessed.
ARTICLE IN PRESS 174 and the world were obtained from Flora Europaea online (http://www.rbge.org.uk/forms/fe.html), the online database from the Germplasm Resources Information Network (GRIN), National Germplasm Resources Laboratory, Beltsville, Maryland (http:// www.ars-grin.gov/npgs/tax/index.html), from Meusel & Ja ¨ger (1992) as well as from recent standard floras. Ecological data were extracted from the Ecological Flora Database of Great Britain (Fitter & Peat, 1994), from Holm, Doll, Holm, Pancho, and Herberger (1997), and from various weed floras and other publications. Climatic match (question 1) was decided by determining the origin of the species and its native distribution. Data on habitats and the ecology of the species (question 11) and local abundance (question 12) were taken from local floras of Switzerland and other regions.
Validation We validated the risk assessment scheme by testing a set of well-known invasive plant species of temperate Europe (Lambinon, 1997; Kowarik & Schepker, 1998; Starfinger, Edwards, Kowarik, & Williamson, 1998), and a set of unsuccessful exotic species in Switzerland. The latter were taken from Lauber & Wagner (1996) and consisted of species which are reported as rarely or occasionally naturalised, and have a restricted range within Switzerland. Accuracies were determined according to Smith, Lonsdale, and Fortune (1999). Accuracy of correctly identifying invasive species is defined as Ai ¼ ðIr =It Þ 100; where Ir is the number of invasive species that were recognised as such by the system, and It is the total number of invasive species tested. Thus, Ai gives the proportion of correct predictions among a set of known invasive species. Similarly, the accuracy of identifying non-invaders is An ¼ ðNa =Nt Þ 100; where Na is the number of non-invasive species correctly predicted as such by the system, and Nt the total number of non-invasive species tested. The overall accuracy Ao is then calculated as Ao ¼ ðNa þ Ir Þ=ðNt þ It Þ: A further useful measure is the likelihood ratio of the prediction method LR ¼ ðIr =It Þ=ðNr =Nt Þ; where Nr is the number of non-invasive species predicted as being invasive by the system. Va-
E. Weber, D. Gut lues41 imply that some predictive ability is present, if LR ¼ 1; then the probability of correctly identifying invasive species is 50%. For further details, see Smith et al. (1999).
Results The risk assessment procedure is given in Appendix A. The results of the validation tests are summarised in Table 1. Out of the 47 invasive plant species tested, 36 were recognised as being invasive in the risk assessment, giving an accuracy of 76.6% (Table 1). The species with the highest scores were Ailanthus altissima, Helianthus tuberosus and Reynoutria japonica (Table 2). Species that were classified by the rating system as requiring further observation included species that are serious plant invaders in some countries (e.g. Rhododendron ponticum and Senecio inaequidens). Species classified as non-invasive were generally species with a restricted geographic distribution. Out of the 193 non-invasive species tested, 119 were recognised as being non-invasive by the risk assessment, leading to an accuracy of 61.6%. Species that are recognised as being potentially invasive by the system include many species with clonal growth, e.g., Sagittaria latifolia, Pontederia cordata, Asclepias syriaca and Glyceria striata (Table 3). The accuracy of correctly predicting non-invasive species (61.6%) was less than the accuracy of correctly predicting invasive species (76.6%). The overall accuracy was closer to 50% than to 100% (Table 1). However, the likelihood-ratio was fairly high (14.8), indicating that the risk assessment has some predictive character. Table 1. Accuracy and likelihood ratio of the risk assessment. For sources of the tested species, see text. Accuracies were calculated according to Smith et al. (1999) Identified as
Invasive plant species
Non-invasive plant species
Low risk Intermediate High risk Total number of species
0 11 36 47
119 64 10 193
(0%) (23.4%) (76.6%) (100%)
(61.6%) (33.2%) (5.2%) (100%)
Accuracy for identifying invasive species: Ai=76.6% Accuracy for identifying non-invasive species: An=61.6% Overall accuracy: Ao=64.6% Likelihood ratio: LR=14.8
ARTICLE IN PRESS Risk assessment system for invasive plants Table 2. Invasive plant species of Europe and their rating as obtained by the risk assessment procedure. For sources of species, see text Species
Sum of scores
Risk class
Ailanthus altissima Helianthus tuberosus Reynoutria japonica Reynoutria sachalinensis Solidago canadensis S. gigantea Arundo donax Epilobium adenocaulon Robinia pseudacacia Bidens frondosa Cornus sericea Heracleum mantegazzianum Rudbeckia laciniata Crassula helmsii Ludwigia grandiflora Acer negundo Elodea canadensis E. densa Ludwigia peploides Lupinus polyphyllus Pinus strobes Prunus serotina Myriophyllum brasiliense Parthenocissus quinquefolia Paspalum distichum Rubus laciniatus Erigeron annuus Impatiens glandulifera Rhus typhina Rumex longifolius Oenothera biennis Rosa rugosa Veronica filiformis Lonicera japonica Rumex confertus Spiraea douglasii Amorpha fruticosa
39 39 39 39
III (High risk) III III III
39 39 37 36
III III III III
36 35 35 35
III III III III
35 34 34 33 33 33 33 33 33 33 32
III III III III III III III III III III III
32
III
32 32 31 31
III III III III
31 31 29 29 29 28 28 28 27
Rhododendron ponticum Galinsoga ciliata Gunnera tinctoria Senecio inaequidens Vaccinium macrocarpon Cyperus eragrostis Impatiens parviflora Physocarpus opulifolius Aster squamatus Lysichiton americanum
27
III III III III III III III III II (further observation) II
26 26 26 26
II II II II
25 25 25
II II II
24 23
II II
175
Discussion The objective of a risk assessment for invasive weeds is to decide which species should be listed on national noxious weed lists and to decide which new species infestations should be controlled or removed in order to prevent their spread and associated ecological consequences. Predicting plant invasiveness is, however, limited due to three facts: (1) the high ecological and taxonomic diversity of invasive plants, (2) the lack of ecological data for most plant species, and (3) the variation in invasiveness within the range of a species. Exotic invasive plants form an extremely heterogenous group of plants comprising of all lifeforms and many families (Daehler, 1998; Pysek, 1998), thus making generalisations about the taxonomic position of invasive plant species difficult. The only conclusion that can be drawn is that certain families are more likely to contribute to invasive plants than other families (Daehler, 1998; Pysek, 1998). The limited amount of available data on the demography and ecology of a species, e.g., relative growth rate, seed weight, length of juvenile period in trees, and crop size, sets serious constraints to the identification of common characters of invasive plant species. Here, databases of basic ecological features among plant species are badly needed, as well as comparative studies under defined conditions and including a wide array of different species (Perrins, Williamson, & Fitter, 1992a). Exotic plant species can be invasive in one part of their introduced range but not in another, thus complicating the decision whether to grant invasive status. Also, the perception of a species as being invasive or not depends on a person’s perspective, and varies between agriculturists and conservationists (Perrins, Williamson, & Fitter, 1992b). Despite these restrictions, the rapidly increasing number of exotic species urgently requires decision-making tools for the management of plant invasions and the regulation of plant trade in order to reduce the risks of new introductions (Sandlund et al., 1999). Existing risk assessments must therefore rely on surrogates for the species’ ecology, and on the experience of the species’ colonisation success in the past. Characters found to be especially suitable are the extent of the geographic range, and whether or not the species shows weedy behaviour elsewhere (Panetta, 1993; Pheloung, 1996). Based on this background, we developed a simple rating system for the identification of invasive plant species in central Europe. Rating systems have proven to be useful in the recognition of pest
ARTICLE IN PRESS 176
E. Weber, D. Gut
Table 3. Unsuccessful exotic plant species in Switzerland, and their ratings as obtained by the risk assessment. Species were taken from Lauber and Wagner (1996) Species
Sum of scores
Sagittaria latifolia Pontederia cordata Artemisia dracunculus Asclepias syriaca Rorippa austriaca Glyceria striata Oenothera parviflora Rumex longifolius Aster lanceolatus Lysimachia punctata Lonicera tatarica Mahonia aquifolium Rubus laciniatus Cyperus eragrostis Sisyrinchium montanum Cynodon dactylon Erigeron karvinskianus Gleditsia triacanthos Lupinus angustifolius Morus alba Salvia verbenaca Sorghum halepense Xanthium spinosum Paspalum dilatatum Typha laxmannii Verbascum phoeniceum Ambrosia artemisiifolia Anethum graveolens Atriplex hortensis Beta vulgaris Chenopodium ambrosioides Dipsacus laciniatus Fagopyrum tataricum Hemerocallis lilio-asphodelus Malva verticillata Nicandra physalodes Nicotiana tabacum
33 32 31 31 31 29 29 29 28 28 27 27 27 26 26 25 25 25 25 25 25 25 25 24 24 24 23 23 23 23 23 23 23 23 23 23 23
mammals (Smallwood & Salmon, 1992) and have been implemented in Australian weed risk assessments (Pheloung, 1996). The proposed risk assessment uses biogeographical and ecological characters that should be fairly easy to obtain. Emphasis was given to the environments in which a new species are expected to occur. The rather low overall accuracy in predicting non-invasives (61.6%) might be due to the low number of species tested, and the variation in degree of invasion among these. However, the likelihood ratio was rather high in our study, indicating that the procedure has some predictive value (Smith et al., 1999). The accuracy of correctly identifying invasive plants of our system
Sum of scores Opuntia humifusa Potentilla fruticosa Rubus phoenicolasius Rumex patientia Rumex thyrsiflorus Silene dichotoma Sorghum vulgare Syringa vulgaris Ulmus laevis Allium scorodoprasum Brassica juncea Diospyros lotus Lycium barbarum Allium fistulosum Amaranthus deflexus Amaranthus graecizans Artemisia annua Avena barbata Bromus diandrus Chrysanthemum segetum Coriandrum sativum Coronopus didymus Cotoneaster horizontalis Cuscuta campestris Galium rubioides Lathyrus sativus Nepeta nepetella Polypogon monspeliensis Ranunculus muricatus Rumex palustris Salvia officinalis Scorzonera hispanica Scutellaria altissima Tolpis barbata Torilis nodosa Tragopogon porrifolius Tribulus terrestris
23 23 23 23 23 23 23 23 23 22 22 22 22 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21
was higher than the accuracy of correctly identifying non-invasive plants. However, since the outcome of any validation depends on the number and kind of species tested, the risk assessment must be tested in practice and further developed as necessary. For example, the answers to the questions of the rating system may be weighted in various ways, influencing the outcome of the system and its accuracy. Further studies are necessary to explore how accuracy changes with different weightings, and whether the accuracy can be improved. The system classified many serious plant invaders of central Europe into the high risk class. There were, however, exceptions. For example,
ARTICLE IN PRESS Risk assessment system for invasive plants Rhododendron ponticum, although considered as a highly invasive species in the British Isles (Fuller & Boorman, 1977) was classified as requiring further observation. This might be due to the restricted ranges, both the native and the introduced. Other exotic species that currently have a very restricted range in Europe were classified into risk class II (intermediate risk). These include many species with clonal growth, e.g., Cyperus eragrostis, Gunnera tinctoria and Lysichiton americanum. Among the unsuccessfully established exotic plant species of Switzerland, species with clonal growth again achieved high scores. Whether these species pose potential problems must be evaluated by studying the ecology of these species. It was not the aim to test the practicability of the rating system. Clearly, such a system must be applied and its practicability evaluated both by scientists and practical experts involved in the management of invasive plants.
Acknowledgements This study was partially funded by the Swiss Plant Protection Foundation. We thank two anonymous referees for valuable comments on the manuscript.
Appendix A. Risk assessment scheme for assessing the invasion potential of environmental weeds in central Europe.
Risk assessment Answer the following questions and sum up the scores given on the right side. If not otherwise indicated, only one answer applies. 1. Climatic match Does the known geographical distribution of the species include ecoclimatic zones similar with those of the risk area? No 0 Yes 2 2. Status of species in Europe Is the species native to Europe? Yes 0 No 2 3. Geographic distribution in Europe In how many countries does the species occur? Species occurs in 0 or 1 country 1 Species occurs in 2–5 countries 2 Species occurs in45 countries 3
177 4. Range size of global distribution How is the size of the global range (native and introduced)? Range is small, species is restricted 0 to a small area within one continent Range is large, extending over more 3 than 151 latitude or longitude in one continent or covers more than one continent 5. History as an agricultural weed elsewhere Is the species reported as a weed from somewhere else? No 0 Yes 3 6. Taxonomy Does the species have weedy congeners? No 0 Yes 3 7. Seed viability and reproduction How many seeds do the species approximately produce? If the species is present in the risk area, this question refers to plants within the risk area. If the species is present in Europe, this question refers to plants within the European range. If the species is not present in Europe, this question refers to the native or introduced range of the species. Few seeds or no viable seeds 1 Many seeds 3 Do not know 2 8. Vegetative growth Allocate species to one of the following. If more than one statement applies, take the one with the highest score. Species has no vegetative growth that leads 0 to lateral spread If a tree or shrub, species has the ability to 2 resprout from stumps or stem layering, or stems root if touching the ground Species has bulbs or corms 1 Species has well developed rhizomes and/ 4 or stolons for lateral spread Species fragments easily, fragments can be 4 dispersed and produce new plants Other or do not know 2 9. Dispersal mode Allocate species to one of the following. If more than one statement applies, take the one with the highest score. Fruits are fleshy and smaller than 5 cm in 2 diameter Fruits are fleshy and larger than 10 cm in 0 length or diameter Fruits are dry and seeds have well devel- 4 oped structures for long-distance dispersal by wind (pappus, hairs, wings)
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Fruits are dry and seeds have well-devel- 4 oped structures for long-distance dispersal by animals (spikes, thorns) Species has mechanisms for self-dispersing 1 Other or do not know 2 10. Lifeform What is the lifeform of the species? Species is a small annual (o 80 cm) 0 Species is a large annual (480 cm) 2 Species is a woody perennial 4 Species is a small herbaceous perennial 2 (o 80 cm) Species is a large herbaceous perennial 4 (480 cm) Species is a free floating aquatic 4 Other 2 11. Habitats of species Allocate species to one of the following. If more than one statement applies, take the one with the highest score. Riparian habitats 3 Bogs/swamps 3 Wet grasslands 3 Dry (xeromorphic) grasslands 3 Closed forests 3 Lakes, lakeshores, and rivers 3 Other 0 12. Population density What is the local abundance of the species? If the species is present in the risk area, this question refers to plants within the risk area. If the species is present in Europe, this question refers to plant within the European range. If the species is not present in Europe, this question refers to the native or introduced range of the species. Species occurs as widely scattered indivi- 0 duals Species forms occasionally patches of high 2 density Species forms large and dense monocul- 4 tures Total score Identify risk class 3–20 Low risk — Species is unlikely to pose a threat to natural communities. 21–27 Intermediate risk — Species requires further observation. 28–39 High risk — Species is likely to become a threat to natural communities if naturalised.
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