A conceptual framework for prioritization of invasive alien species for management according to their impact

Prioritization tool for IAS management 69 A conceptual framework for prioritization of invasive alien species for management according to their impact Sabrina Kumschick1, Sven Bacher2, Wayne Dawson3, Jaakko Heikkilä4, AgnieszkaSendek5, Therese Pluess2, Tamara B. Robinson1, Ingolf Kühn5 1 Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Matieland, 7602, South Africa 2University of Fribourg, Department of Biology, Ecology & Evolution Unit, Ch. du Musée 10, 1700 Fribourg, Switzerland 3Ecology, Department of Biology, Universitätsstrasse 10, Konstanz, D 78464, Germany 4MTT Agrifood Research Finland, Economic Research, Latokartanonkaari 9, 00790 Helsinki, Finland 5UFZ, Helmholtz Centre for Environmental Research – UFZ, Dept. Community Ecology, Theodor-Lieser-Str. 4, 06120 Halle, Germany Corresponding author: Sabrina Kumschick ([email protected]) Academic editor: U. Starfinger|Received 7 December 2012|Accepted 11 December 2012|Published 14 December2012 Citation: Kumschick S, Bacher S, Dawson W, Heikkilä J, Sendek A, Pluess T, Robinson TB, Kühn I (2012) A conceptual framework for prioritization of invasive alien species for management according to their impact. NeoBiota 15: 69–100. doi: 10.3897/neobiota.15.3323 Abstract The number of invasive alien species is increasing and so are the impacts these species cause to the environment and economies. Nevertheless, resources for management are limited, which makes prioritization unavoidable. We present a prioritization framework which can be useful for decision makers as it includes both a scientific impact assessment and the evaluation of impact importance by affected stakeholders. The framework is divided into five steps, namely 1) stakeholder selection and weighting of stakeholder importance by the decision maker, 2) factual description and scoring of changes by scientists, 3) evaluation of the importance of impact categories by stakeholders, 4) calculation of weighted impact categories and 5) calculation of final impact score and decision making. The framework could be used at different scales and by different authorities. Furthermore, it would make the decision making process transparent and retraceable for all stakeholders and the general public. Keywords stakeholder, decision maker, exotic, generic scoring system, impact, value Copyright Sabrina Kumschick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. NeoBiota 15: 69–100 (2012) doi: 10.3897/neobiota.15.3323 www.pensoft.net/journals/neobiota Review ARtiCle Advancing research on alien species and biological invasions A peer-reviewed open-access journal NeoBiota Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 70 introduction Impacts of invasive alien species (IAS) affect different receptor environments, and are often divided into environmental and socio-economic impacts. Some of these impacts can result in substantial monetary costs and/or alterations to entire ecosystems and social systems (O’Dowd et al. 2003, Pimentel et al. 2005, Reaser et al. 2007, Vilà et al. 2010). At an international level the ecological impacts of IAS are addressed by the Convention on Biological Diversity (CBD 1992). Through this convention the need for prioritization and management of priority species has been highlighted in the Strategic Plan for Biodiversity 2011-2020 (COP 10 2010), although no guidance on how to achieve this ideal is provided. There has been recognition that societies need to mitigate negative impacts of IAS, i.e. find appropriate means to manage IAS in a way that their impacts are at least minimized, e.g. by eradication, reduction below a specific threshold, or containment. However, resources to manage IAS are limited and with increasing globalization, the influx of potentially harmful organisms will likely continue to increase (Perrings et al. 2010, Essl et al. 2011). There are two approaches to this problem. Firstly, to limit new alien species from entering an area/country, for which purpose border control risk assessments have been developed (e.g., Pheloung et al. 1999, Bomford 2008, see Hulme 2012 and Leung et al. 2012 for reviews). Secondly, alien species that escape border controls (Bacon et al. 2012) or have never been subjected to border control risk assessment, and which cause high impact must be managed in their new ranges (see above). Hence, a system is needed that facilitates the optimal allocation of limited resources to manage those IAS that are most harmful in a given area. Such a system would ideally integrate the severity of effects on the environment, as well as on the economy and the society in question, allowing decision makers to prioritize certain high impact species for management. However, also cost-effectiveness of management needs to be taken into account. Alien species, however, do not have only negative effects. The majority of the alien plants in Europe were deliberately introduced, e.g. as ornamental, horticultural, restoration, agricultural or forestry species (Hopper 2007, Lambdon et al. 2008, Pyšek et al. 2009) with their respective social, economic and environmental benefits. Management of such species, which are detrimental in some aspects (e.g. for biodiversity) and beneficial in others (e.g. forestry), can result in conflicts among involved stakeholders. For example, the introduction to South Africa of alien Acacia species which subsequently became invasive had differential effects on local communities. On the one hand, communities suffered from water scarcity due to increased evapotranspiration by the acacias. On the other hand, they benefitted from fuel wood and building timber (De Wit et al. 2001). Such situations have led to the recognition of a need for a framework to document the different consequences of an IAS for different groups of stakeholders (Stoll-Kleemann and Welp 2006, Binimelis et al. 2007, Kapler et al. 2012) and recently a few attempts have been made to develop applications which incorporate Prioritization tool for IAS management 71 stakeholders (Cook and Proctor 2007, Hurley et al. 2010, Liu et al. 2011, De Lange et al. 2012, Forsyth et al. 2012). Parker et al. (1999) developed a framework to assess the ecological effect of IAS, arguing that the total effect of an invader includes three fundamental dimensions: range, abundance, and the per-capita or per-biomass effect of the invader, i.e. the magnitude of ecological change it causes. Since then progress has been made in scoring the overall negative effects of alien species (e.g., Nentwig et al. 2010, Kumschick and Nentwig 2010, Pluess 2011). A very detailed assessment scheme for impacts of genetically modified organisms was presented by Kowarik et al. (2008) which can easily be adapted for invasive species. However, few of these impact scoring approaches explicitly addressed potentially competing interests of stakeholders (i.e. various ecological, economic or social interests) within the context of management of IAS. Furthermore, these studies ignore potential positive effects of IAS, which might be crucial for some species and stakeholders (see e.g., Schlaepfer et al. 2011 for a review). These points are important because biological invasions represent a complex societal issue for two reasons. First, the scientific knowledge about biological invasions and the outcome of different management options are highly uncertain and second, both conflicts of interests and values are prominent in a problem-solving context such as the management of IAS (Kueffer and Hadorn 2008). Thus, as in any environmental decision making process, IAS management has to minimize conflicts characterized by ecological, economic and social value judgments of different stakeholders (Liu et al. 2010, 2011). Furthermore, if all types of impacts of IAS are to be assessed (i.e. ecological and socio-economic impacts), then the different scientific disciplines and associated value systems require a common currency with which to measure impact. Another layer of complexity is added by the fact that different sections of administration and stakeholder groups with differing agendas need to be integrated, since plants, animals and human health are in the responsibility of different agencies and/or ministries (e.g., IPPC - International Plant Protection Convention, OIE - World Organization for Animal Health, WHO - World Health Organization). At present, several studies have proposed prioritization methods for the management of weeds (e.g., Skinner et al. 2000, Virtue et al. 2001, Robertson et al. 2003, Tassin et al. 2006, Randall et al. 2008, Brunel et al. 2010). However, only few schemes considered potential conflicts of interest when evaluating which weed species to prioritize for control first, mainly in South Africa (Robertson et al. 2003, Forsyth et al. 2012, De Lange et al. 2012). Other studies that specifically tackled the complexities of conflicting interests and values in IAS management have usually focused on particular outbreak situations of a single species (Maguire 2004, Liu et al. 2010, 2012). Based on a participatory approach in Western Australia, the prioritization by an assessment committee differed from current resource allocations in Western Australia (Cook and Proctor 2007). A similar approach was taken by Roura-Pascual et al. (2010) for South Africa. However, such a potentially time-consuming and re- Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 72 source-demanding approach might not always be possible. Hence, decision makers and especially governmental bodies are still in need of a generic decision making aid that facilitates the identification of priority species whilst minimizing or reconciling potential conflicts of interest. The basic problem with many of the systems to date is a fundamental one. Decisions made for IAS management are heavily influenced by judgements which are predominantly based on inputs from scientists (Wilhere 2008). In general, the role undertaken by scientists in decision making falls along a gradient (Lach et al. 2003). At one end of the continuum, scientists may simply report results that others use to make decisions. Alternatively, they may interpret these results and work with decision makers to integrate these results into the decision making process. At the other end of the continuum, scientists may be actively involved in decision making by advocating for a specific decision or in the extreme, making the decision themselves. While traditionally scientists largely shied away from active involvement in decision making (Lach et al. 2003), recent years have seen increasing advocacy (Marris 2006, Scott et al. 2007). This has resulted in a call for science inputs into decision making to be supportive of the process but dispassionate towards policy outcomes (Lackey 2007), recognising that science is but one vital element that needs to be considered in decision making. Against this background we argue that the process of objectively describing with scientific methods changes associated with an IAS has to be explicitly separated from the proximate subjective societal evaluation of impact, which is based on values. For the actual decision making for management, however, facts (effects on environment and socio-economy) need to be connected to values (judgement of involved stakeholders). Here, we propose a comprehensive framework which aims to explicitly separate the scientific description of changes caused by IAS from the value systems of affected stakeholders who may have differing interests. Furthermore, it addresses both negative and positive effects of IAS, since positive effects are often neglected in purely ecological impact studies (Goodenough 2010, Davis et al. 2011, but see Pyšek et al. 2012 for a global review). Framework for impact evaluation of iAS The framework suggested here is divided into five steps. The different steps are shortly introduced in this section. We then present more details about the scorings and values in the following sections and in Figures 1 and 2. Step 1: Stakeholder selection and weighting of stakeholder importance. A call for stakeholder participation is launched and they are encouraged to claim their interest. The stakeholder group is formed such that it is sufficiently representative and Prioritization tool for IAS management 73 appropriate for the task at hand. The participating stakeholders are then categorized according to their importance in relation to the issue that is being evaluated. This process produces Stakeholder Weights (SW), and should be conducted in a transparent and logical way. Step 2: Description and scoring of changes due to IAS. For this step we propose a scoring system, based on two main impact classes (ecological, socio-economic) each with several categories (e.g., agriculture, health, infrastructure, herbivory, hybridization). Negative and positive changes are separately evaluated for each IAS. The outcome of this step is hereafter referred to as Change Assessment Score (CAS). Step 3: Valuing the relative importance of impact categories by stakeholders. After identifying affected stakeholders in step 1, each stakeholder values the relative importance of all impact categories. Negative and positive categories are valued separately. When valuing the categories, the stakeholders do not know the species assessed in step 2 and their change assessment scores. This is called Stakeholder Value Assessment (SVA). After selection of stakeholders (step 1), the description of changes (step 2) and the assessment of stakeholder weights (step 3) can be conducted at the same time as one does not depend on the outcome of the other. The following steps in turn can only be performed if the outcomes of the former steps are known. Figure 1. Schematic overview of the conceptual framework to assess change in different impact categories for each species, capture stakeholders’ interests and weigh stakeholders and calculate a final impact score for each species, see chapter “framework for impact evaluation” of IAS for a brief and the following chapters for detailed explanation. Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 74 Step 4: Calculating weighted impact categories. This is done by combining the outcomes of step 1 and step 3, which produces Weighted Impact Categories (WIC). Step 5: Final impact scores. The Final Impact Scores (FIS) for each species are calculated by combining the CAS (step 2) with WIC (step 4). In the following sections, the five steps are described in detail, and in the final part of the paper the usefulness of the scheme for different potential end-users and advantages and potential shortcomings are discussed. Figure 2. Fictitious example on how to calculate the different values of the prioritization framework. For brevity, we limit the number of categories from the scientific impact assessment in Step 2 of the framework to 3 (out of 24). Species 2 has the highest social Change Assessment Score (CAS), whilst species 3 has the highest CAS for ecosystem changes. The decision maker gives stakeholder Y the greatest weighting. In the Stakeholder Value Assessment (SVA), stakeholder X gives the greatest value to ecosystem, whilst Y values the social category the highest, and stakeholder Z values agriculture most. Multiplying these values by the stakeholder weights and summing the products gives Weighted Impact Categories (WIC), and multiplying these values by respective category CAS values gives the final overall impact scores per species. Note that WIC values for positive change need to be inversed to negative values upon calculation of final impact scores per category and overall. Prioritization tool for IAS management 75 Step 1: Stakeholder selection and weighting of stakeholder importance Stakeholders play a central role in the presented scheme, as their opinions are crucial for evaluating the subjective impact categories through formal and structured analysis. The stakeholder process needs to be carefully planned, structured and conducted, accounting for the aim and needs of the problem at hand (Renn and Schweizer 2009). There are three main things to consider: a) who should participate; b) what is the form of the participatory process; and c) whose opinion counts. Who should participate? A stakeholder is – put simply – someone who can affect or is affected by the issue at stake (Freeman 1984, cited in Mitchell et al. 1997). There are several methods available that one could use to come up with a list of stakeholders (see, e.g. Pretty 1995, Reed et al. 2009). For instance, an often-applied method is the so called ‘snowball technique’ which involves consulting every stakeholder as long as no new actors are indicated. How representative the stakeholder group should be depends on the aim of the process (e.g. Rowe and Frewer 2005, Webler and Tuler 2006, Reed 2008, Renn and Schweizer 2009, Wesselink et al. 2011). For instance, the aim of the stakeholder process may be to avoid missing information and perspectives, to try to find win-win situations or compensations from winners to losers, to represent and discuss all relevant arguments, to ensure that less-privileged groups are given the opportunity to have their voices heard, or to enlighten policy processes by illustrating the diversity of claims, opinions and values (Renn and Schweizer 2009). We suggest that at least all those who are potentially affected by the species should have a possibility to participate or have their voice heard through some other participant (e.g. an organization). In practice, stakeholders would consist of, for instance, agricultural and silvicultural producers, environmental organizations, tourist industry, city/town representatives, different outdoor associations (e.g. hunters, bird-watchers, recreationists), and so forth. table 1. Prioritizing scheme in five steps, describing the action taken at each step, identifying the actor of each step and defining the output of each step. *) can be performed simultaneously. Step Action Actor Output 1) Decision maker chooses the stakeholders and decides on the form and execution of the weighting process Decision maker SW = Stakeholder Weights 2*) Assessment of change: the change a species incurs for each category from App. A is scored Scientists CAS = Change Assessment Score 3*) Stakeholders value each category from App. A, regardless of the species and change a species incurred Stakeholders SVA = Stakeholder Value Assessment 4) Calculation of weighted impacts by combining SVA × SW Decision maker (or scientists or consultant) WIC = Weighted Impact Categories 5) Calculation of final impact score WIC × CAS Decision maker (or scientists or consultant) FIS = Final Impact Score Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 76 What is the form of the participatory process? One main issue regarding the stakeholder process is the form of opinion-forming: is the process aiming at a consensus through deliberation, or are the stakeholders just asked for their individual opinion? If a consensus is sought for, the result of the process in our case would be a single set of weights (see step 3) that could directly be used to weigh the species impacts (resulting from step 2). If each stakeholder is allowed to have their own weights, then these need to be aggregated in some way unless the analysis is to be conducted separately for each stakeholder. A simple way is to average all the weights, in which case each stakeholders’ opinion is valued equally. However, if the decision maker wishes to weigh the stakeholder opinions, specific weights for each stakeholder need to be produced. Whose opinion counts? There are both ethical and pragmatic reasons why the decision maker should attend more closely to some stakeholders than others (Colfer et al. 1999). These include fair treatment of those who are more affected by the decision, and that some stakeholders just have a greater likelihood than others of affecting (and being affected by) the issue at stake. There are theories that attempt to explain, often in business context, which stakeholders are being paid more attention to (Reed et al. 2009). One such theory is the theory of stakeholder salience (Mitchell et al. 1997), according to which stakeholders can be categorized using three attributes: power (to affect the decision maker), legitimacy (to the issue at stake), and urgency (of their claims). The more of these three properties a stakeholder has, the higher is their salience and hence their importance in the eyes of the decision maker. Categorization provides the decision maker with the possibility to influence the prioritization procedure by weighting each of the participating stakeholders. As this may be considered as a source of bias, it should be transparent and ideally based on objective and reliable analysis of stakeholders’ attributes (Mark and Shotland 1985, Mushove and Vogel 2005). For instance, Colfer et al. (1999) suggest seven criteria by which to define the most important stakeholders in the case of forest management, score them at a scale 1-3 for each criterion and obtain a weight for each stakeholder by averaging over the criteria. Alternatively there exist for instance pairwise comparison methods (Grafakos et al. 2010) that may be used to produce the required weights. Weighting is not a straightforward process, especially when numerous attributes of the stakeholders are taken into consideration, and when stakeholders’ external environment and interactions are complex (de Reynier et al. 2010, Aaltonen 2011). The decision maker undertaking the categorization (“top-down approach”) is by no means the only way of attributing a weight to stakeholders. There are also methods through which the stakeholders themselves come up with a ranking order of their importance (see, for instance, Pretty 1995, Mitchell et al. 1997, Reed 2008, Reed et al. 2009). Prioritization tool for IAS management 77 Reed (2008) provides best practices for the stakeholder process, including for instance emphasis on empowerment and equity, representation and analysis of relevant stakeholders, need for clear objectives for the process, choosing methods depending on the context, and integration of scientific and local knowledge. Our framework requires the evaluation and categorization of stakeholder importance. However, as to what the precise format of the stakeholder process should be, we do not specify here for reasons of space. Practical examples in the context of invasive alien species can be found in Cook and Proctor (2007), Hurley et al. (2010), Skurka Darin et al. (2011) and De Lange et al. (2012). The desired outcome nonetheless is clear: the process should produce a set of weights for the different impact categories that would broadly reflect the values present in the society. Step 2: Description and scoring of changes The second step of the decision making process aims at recording all changes an IAS causes in the introduced range. An impact or change in this case is defined as any deviation from the state of a system before the invasion happened. In order to make comparison between species, different locations and different measurements of impact, we suggest the use of a generic scoring system (e.g., Nentwig et al. 2010, Kumschick and Nentwig 2010). Nevertheless, scoring systems and other prioritization tools suggested so far often only focus on unwanted changes and rarely take into account possible welcome changes which might result from species introductions, as e.g. increasing population densities of threatened native species (Schlaepfer et al. 2011) or economic benefits (Leung et al. 2012). For a balanced view, however, positive effects should no longer be neglected or even ignored, as many stakeholders profit from such IAS. When a decision is needed on how to deal with an IAS, all possible stakeholder interests need to be accounted for to ensure wide acceptance and support for the decision (Myers et al. 2000, Gardener et al. 2010; see step 1 for more details). However, whether changes are perceived as “positive” or “negative” depends on the value system of the stakeholders concerned (Simberloff et al. 2012). For example, the invasion of the weed Paterson’s Curse (Echium plantagineum) in Australia was perceived as detrimental by ranchers because the plant is toxic to livestock, but beekeepers profited from its proliferous honey production (Harris 1988). In the following description of impact (changes), we continue to use the terms “positive” and “negative”, but aim to define them in an objective, value-free way by describing the direction of change relative to pre-invasion state of the system. Based on previously published scoring systems (e.g., Nentwig et al. 2010, Kumschick and Nentwig 2010, Kumschick et al. 2011, Pluess 2011, Kumschick et al. 2012), we determined a wide range of changes IAS could cause in the introduced area (Appendix A). The scoring system consists of two main classes of changes, socioeconomic and environmental, and each class has 6 categories. 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Environmental impact 1.1.1 Herbivory/toxicity negative 0 No impact known or detectable. 1 Very low level of herbivory (animals) or toxicity (plants or animals) on at least one native species, no major damage reported. 2 Herbivory or toxicity affecting several native species, without large impact on affected species or decline of their populations. 3 Herbivory or toxicity affecting several native species, at least one native species declining. 4 Herbivory or toxicity affecting many native species, several declining in population size, recorded community change reversible. 5 Herbivory or toxicity affecting native species listed as vulnerable, endangered or critically endangered by IUCN, decline of these species, replacement or even extinction of species, recorded community change irreversible. 1.1.2 Herbivory/toxicity positive 0 No impact known or detectable. +1 Very low level of herbivory or toxicity affecting at least one species degrading the ecosystem, no impact on performance of affected species recorded. +2 Herbivory or toxicity affecting one or several species degrading the ecosystem, without large impact on affected species or decline of their populations. +3 Herbivory or toxicity affecting one or several species degrading the ecosystem, at least one species declining, some/first indications that the ecosystem changes towards its historical functional state. Prioritization tool for IAS management 91 +4 Herbivory or toxicity affecting one to many species degrading the ecosystem, declining in population size, strong indications that the ecosystem changes towards its historical functional state. +5 Complete re-establishment of functional state of historical ecosystem that was degraded before invasion of alien species. 1.2.1 Competition negative 0 No impact known or detectable. 1 For animals, very low level of competition with at least one native species, exploitation competition; for plants, low abundance, native species richness not declining. 2 For animals, competition with several native species by exploitation competition, without large impact on affected species or decline of their populations; for plants, moderate abundance, decrease in native species abundance but not richness. 3 For animals, competition with several species, interference competition, at least one native species declining; for plants, high abundance, decrease in native abundance, at least one native species lost. 4 For animals, competition with many native species, several declining in population size, competition for food and/or space, behavioural changes in out-competed species; for plants, high abundance, strong decline in both abundance and richness of native species, native species still able to recruit. 5 For animals, competes with species listed as vulnerable, endangered or critically endangered by IUCN, decline of these species, replacement or even extinction of species; for plants, mono-dominant/near mono-dominant, with no or very few native species remaining; limiting native species recruitment options. 1.2.2 Competition positive 0 No impact known or detectable. +1 For animals, very low level of competition with at least one native species degrading the ecosystem, exploitation competition, no impact on performance of affected species recorded; for plants, no loss in abundance or richness of native species. +2 For animals, competition with one or several native species degrading the ecosystem by exploitation competition, without large impact on affected species or decline of their populations; for plants, small increase in abundance of native species, no increase in species richness. +3 For animals, competition with one or several species degrading the ecosystem, interference competition, at least one species declining, some indications that the ecosystem changes towards its historical functional state; for plants, increase in abundance of native species, small increase in species diversity. Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 92 +4 For animals, competition with one to many species degrading the ecosystem, declining in population size, strong indications that the ecosystem changes towards its historical functional state; for plants, increase in abundance of native species and in species diversity. +5 For animals, completely re-establish functional state of historical ecosystem that was degraded before invasion of alien species; for plants, increase in abundance of native species and in species diversity, including threatened native species. 1.3.1 Predation negative (not relevant for plants) 0 No impact known or detectable. 1 Predation known but negligible, no decline of native species. 2 Predation on several abundant species, without large impact on affected species or decline of their populations. 3 Decline of one to several native species recognized, minor change in food web structure reported. 4 Decline of many species, indirect impact by mesopredator release, clear changes in the food web. 5 Preys also on endemic or species listed as vulnerable, endangered or critically endangered by IUCN, local extinction. 1.3.2 Predation positive (not relevant for plants) 0 No impact known or detectable. +1 Predation on species degrading the ecosystem known but negligible, no decline of species. +2 Predation on one or several species degrading the ecosystem, without large impact on affected species or decline of their populations. +3 Decline of one to several native species degrading the ecosystem recognized, minor change in food web structure reported, some indications that the ecosystem changes towards its historical functional state. +4 Decline of one to many species degrading the ecosystem, clear changes in the food web, strong indications that the ecosystem changes towards its historical functional state. +5 Completely re-establish functional state of historical ecosystem that was degraded before invasion of alien species. 1.4.1 Transmission of diseases to wildlife negative 0 No impact known or detectable. 1 Host (plant or animal) for non-specific parasites, occasional transmission of more or less harmless diseases to one native species. No population decline in native species. If a plant, species is not a breeding ground for wildlife disease vectors. Prioritization tool for IAS management 93 2 Occasional transmission of more or less harmless diseases, several native species affected. No or only minor population decline in native species. If a plant, species may be a breeding ground for wildlife disease vectors, but no more so than native plant species. 3 Many native species affected, frequent transmission of more or less harmless diseases or harmful diseases transmitted to one native species. Minor population decline in native species. If a plant, may be a more significant breeding ground for wildlife disease vectors than native plant species. 4 Transmits harmful diseases to several native species or more or less harmless diseases to endemic or species listed as vulnerable, endangered or critically endangered by IUCN. Moderate population decline in native species. If a plant, a major breeding ground for wildlife disease vectors, outbreaks due to species presence uncertain. 5 Transmits harmful diseases to many species and/or species listed as vulnerable, endangered or critically endangered by IUCN by direct transmission, decline of these species or extinction. If a plant, a major breeding ground for wildlife disease, outbreaks due to species presence certain. 1.4.2 Transmission of diseases to wildlife positive 0 No impact known or detectable. +1 Occasional transmission of more or less harmless diseases to one species degrading the ecosystem; no population decline in species. Potential positive effect on health of wildlife (direct: e.g. potential medicinal species; indirect: e.g. antagonist of a health threat), but not yet reported. +2 Occasional transmission of more or less harmless diseases, one or several species degrading the ecosystem affected. No or only minor population decline in species. Occasional, small positive effect on health of wildlife. +3 One to many species degrading the ecosystem affected, frequent transmission of more or less harmless diseases or harmful diseases transmitted to one species degrading the ecosystem. Minor population decline in species, some indications that the ecosystem changes towards its historical functional state. Regularly small positive effect on health of wildlife, or occasional, larger positive effect on health of wildlife. +4 Transmits harmful diseases to one to several species degrading the ecosystem. Moderate population decline in species, strong indications that the ecosystem changes towards its historical functional state. Regularly leading to larger positive effect on health of wildlife. +5 Completely re-establish functional state of historical ecosystem that was degraded before invasion of alien species. Massive positive effect on health of wildlife caused by species. Sabrina Kumschick et al. / NeoBiota 15: 69–100 (2012) 100 2.6.2 On human social life positive 0 No impact known or detectable. +1 Biological traits and life-style suggest potential positive effect for recreational or residence areas (e.g. charismatic or decorative species, species ameliorating the environment by providing e.g. shade, or having edible parts, or species potentially used for angling or hunting), but not reported so far. +2 Occasional small positive effect for recreational or residence areas, only small percentage of human population affected. +3 Regular small positive effect for recreational or residence areas, or occasional larger positive effect for recreational or residence areas. +4 Regular larger positive effect for recreational or residence areas. Recreational value of a habitat or a landscape strongly increased. +5 Massive positive effect for recreational or residence areas. Massive gain of recreational value of a habitat or a landscape.