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A global review of target impact and direct nontarget effects of classical weed biological control
Journal Pre-proof A global review of target impact and direct nontarget effects of classical weed biological control ¨ Hariet L Hinz, Rachel L Winston, Mark Schwarzlander
PII:
S2214-5745(20)30009-2
DOI:
https://doi.org/10.1016/j.cois.2019.11.006
Reference:
COIS 654
To appear in:
Current Opinion in Insect Science
¨ Please cite this article as: Hinz HL, Winston RL, Schwarzlander M, A global review of target impact and direct nontarget effects of classical weed biological control, Current Opinion in Insect Science (2020), doi: https://doi.org/10.1016/j.cois.2019.11.006
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A global review of target impact and direct nontarget effects of classical weed biological control
Hariet L. Hinz1*, Rachel L. Winston2, and Mark Schwarzländer3
CABI, Rue des Grillons 1, 2800 Delémont, Switzerland
2
MIA Consulting, Shelley, ID 83274, USA
3
Department of Entomology, Plant Pathology and Nematology, University of Idaho, Moscow,
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1
ID 83844-2339, USA
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Corresponding author: Hariet L. Hinz, [email protected], ORCID ID: 000-0003-2930-6807
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Highlights
~1/4 weed biocontrol projects resulted in complete control
Measures of biocontrol success should be context specific
Direct nontarget attack (NTA) incidence and severity are decreasing over time
Pre-release testing predictions for NTA are more than 99% accurate
Post-release monitoring should be quantitative, targeted, and long-term
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Abstract
Recent reviews show that classical weed biocontrol can be successful in reducing the negative impacts of invasive plant species, have impressive returns on investment, and contribute to slower rates of weed spread. Quantitative post-release monitoring is necessary to account for differences in biocontrol outcomes across spatial and temporal scales. Direct
nontarget attack (NTA) incidence and severity are decreasing over time, and pre-release hostspecificity tests can accurately predict NTA post-release, as long as the nontarget plant species are included in testing. Less than 1% of NTA was found where the impacted plant species had been tested pre-release and was deemed not at risk. Effectiveness and environmental safety will likely further improve with the incorporation of new technologies, such as experimental evolutionary studies.
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Introductions
Two questions central to the discipline of classical biological control of weeds have been
debated for some time. These are a) whether the practice provides measurable successes in
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controlling target plants [1, 2] and b) whether it is environmentally safe [3, 4]. In contrast,
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there is consensus on the untenable lack of quantitative post-release monitoring data [2, 4]. However, in recent years, progress has been made to fill this gap in regions that are most
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invested in weed biocontrol [5, 6, 7, 8, 9, 10, 11]. Advancements in molecular technologies, such as techniques to identify cryptic species [e.g. 12] and genetic diversity in
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the weed system [13] or the use of molecular phylogenies to develop test plant lists and interpret results of host-specificity tests [14], are now routinely incorporated in biocontrol
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projects, which improves the probability of their success and the predictability of their safety. Other novel experimental approaches are currently being explored, for instance, behavioural
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ecology coupled with electro-physiological studies to predict host choice of biocontrol agents [15], or investigations on rapid evolutionary changes [16]. Our objectives here are to summarize recent reviews regarding the effectiveness and safety record of classical biological weed control, to synthesize the most important findings, and to outline continuing challenges. We conclude with an outline of future research directions to further advance biological weed control.
Effectiveness of biological control of weeds Several studies evaluating biological weed control outcomes used the definitions provided by Hoffmann [17], who distinguishes a) complete control, where no other control methods are needed to supress the weed, b) substantial control, where other control measures can be substantially reduced, and c) negligible control [18, 19, 20, 21]. Data used in these studies were derived from published literature but typically also included expert opinion. According to these evaluations, approximately 25% of biocontrol projects have achieved complete
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control, and 50–70% of biocontrol projects have achieved at least substantial control,
depending on the country and/or region where outcomes were assessed. In New Zealand, at least partial control was achieved for 47% of weed biocontrol projects [22].
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Schwarzländer et al. [1], who used Winston et al. [23] as the basis for their assessment,
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applied similar success criteria, but also estimated the success of each intentionally released biological control agent as well as of each individual release (taking into account that most
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biocontrol agents were released in different countries/regions, at various times, and against different target weeds). The latter, in particular, helped expose potential reasons for the
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success or failure of an agent in controlling a specific target weed in a specific region or country of release [23]. Success rates were similar for agent species and individual releases,
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with approximately 50% of both resulting in some level of control (variable, medium, or heavy impact; for definitions see Schwarzländer et al. [1]) and approximately 25% resulting
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in heavy impact (Fig. 1); 66% of weeds targeted experienced at least some level of control [1].
These measures of success have been criticized for being subjective and qualitative in nature, and because they are lacking benchmarks or controls to which biocontrol outcome data could be compared [2, 24, 25]. Benchmarks can be obtained by monitoring several pre-selected field sites prior to release of the biocontrol agent [e.g. 26], and control plots can be
established when planning agent releases. However, because some agents disperse rapidly, keeping control plots free from attack can be difficult [27]. Insecticides or fungicides have been used successfully to this end [8, 28, 29], but they also alter the control plot ecosystem by eliminating nontarget insects and/or soil fungi [30] and may have direct effects on the target weed [31]. Exclosure studies and other set design experiments do establish cause and effect relationships and can provide valuable insights into mechanisms of successful weed management and interactions of herbivory with other biotic factors, but they are often limited
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in duration and spatial scale (one or a few sites) [e.g. 5, 8, 32]. Results, therefore, cannot necessarily be extrapolated to the landscape or regional scale, at which biocontrol acts.
Alternatively, long-term (>5 years) post-release monitoring studies over large spatial scales,
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even when lacking control sites, can estimate effects of biocontrol agents on weed population growth rates while taking into account stochastic events and spatial and temporal variability
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of biocontrol success [e.g. 9, 11, 33, 34, 35, 36]. Weed and Schwarzländer [36] used a
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discrete model of the population dynamics for Dalmatian toadflax, Linaria dalmatica (L.) Mill., and found that ramet density of the plant was negatively affected by stem density in the
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prior year and abundance of the weed biocontrol agent Mecinus janthiniformis Toševski & Caldara, and positively affected by precipitation.
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In a recent extension of the criteria originally suggested by Hoffmann [17], Hoffmann et al. [7] proposed documenting outcomes of biological weed control at the population level
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through quantification of four different invasion parameters: 1) weed density, 2) area occupied, 3) biomass of the weed, and 4) number of propagules. The authors emphasized the context-specific nature of weed biocontrol and proposed recording outcomes in different regions and for different habitats (e.g. drylands, riparian). Other measures of success use economic and ecological benefits accrued by biocontrol. Economic benefits have traditionally been expressed as cost:benefit ratios. These have varied
from 2.3–4,000 for various weed systems [37, 38]. In Australia, for example, every dollar invested in weed biocontrol projects provided average benefits of $23.10 [39]. If the overall costs of a weed are high, economic benefits of weed biocontrol projects (cost:benefit ratios >1) are readily achieved, even at very modest levels of control, because costs for biocontrol tend to be low compared to other control methods [40]. Similarly, biocontrol success has also been measured based on the reduction in the target weeds’ impact. Hill and Coetzee [6] used the generic impact scoring system (GISS) proposed by Nentwig et al. [41] to assess the
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impact of eight water weeds in South Africa before and after biological control. The introduction of biocontrol agents drastically reduced the environmental and socio-economic impact scores for four of the five most serious exotic aquatic weeds [6].
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It has also been proposed that success of biocontrol projects should be measured as a
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decrease in the finite population growth rate (lambda) of the target weed or in its equilibrium population size using demographic modelling [2, 42, 43]. This has rarely been done in weed
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biocontrol [but see 5, 32, 44, 45]. For some invasive trees and shrubs, it has been shown that seed-feeding biocontrol agents would need to destroy close to 100% of seeds to reduce
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lambda to <1 [46]. Nonetheless, biocontrol agents that reduced seed production of several invasive Acacia shrubs and trees by less than 100% still contributed to successful control by
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making manual and chemical control strategies economically viable [47]. Even if weed biocontrol agents do not reduce weed stand densities, they can still slow rates of spread and
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curb range expansion of invasive plant populations [48, 49]. For example, an analysis of the Southern African Plant Invaders Atlas, which documents alien plants growing outside of cultivation since 1994, found that although the number of quarter-degree squares occupied by alien plants increased by approximately 50% between 2000 and 2016, classical biological control programs reduced the rate of spread of some taxa and, in a few cases, led to range contractions, while other interventions (mechanical, chemical) had no detectable effect [50].
Environmental safety of biological control of weeds In the following, we focus on direct NTA because indirect effects, regardless of whether detrimental or beneficial, are difficult to predict and have thus far rarely been assessed for weed biological control [51, 52]. The extent of direct NTA caused by biological control agents varies substantially with outcomes ranging from negligible to negative effects at the population level. In a recent review, Suckling and Sforza [53] accounted for the magnitude of NTA by proposing a scale
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from ‘minimal’ to ‘massive’, covering effects impairing nontarget plant individuals,
populations, communities, and ecosystem processes. Alternatively, Hinz et al. [4] used
persistence of NTA in their review as the main criterion assessing its severity. They defined
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three categories: ‘collateral’, ‘spillover’, and ‘sustained’ direct NTA (Box 1). Using this
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categorization, the authors concluded that only sustained direct NTA is likely to lead to population-level effects [4]. Blossey [42] argued that nontarget effects should only include
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cases where the finite growth rate (lambda) of a nontarget population has been supressed to <1 as the result of successful establishment of a biological control agent. This would,
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however, require that demographic modelling data exist for the nontarget plant species, which is rarely the case [but see 54, 55, 56], because the laborious and difficult process of collecting
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demographic modelling data has already limited these studies for target weed species.
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Suckling and Sforza [53] and Hinz et al. [4] both found that, based on available data, less than 1% of all classical weed biocontrol agent releases to date have the potential to lead to negative population-level nontarget effects. The three most severe cases identified in both reviews are listed in Table 1. All three biocontrol agents have in common that their releases occurred in the 1950s and 1960s when release protocols for weed biocontrol agents did not consider the risk to native species.
In their review, Hinz et al. [4] used releases made through 2008. Utilizing the more recently updated Winston et al. [57], we report herein data for releases made through 2016, as this was the most recent release known to have resulted in NTA. Of 493 agents intentionally released through 2016, 62 (12.6%) have been recorded attacking nontarget species in the field, two more than in the recent review by Hinz et al. [4]. Of 1,623 releases made using the 493 agent species, 124 (7.6%) resulted in NTA. Both the proportions of agent species and releases with NTA have declined over time (Fig. 2). This either suggests that methods to
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determine the environmental safety of weed biocontrol agents have improved over time, or that regulations to import agents have become stricter, or a combination of both. Overall, intentionally released biocontrol agents caused 12% collateral, 51% spillover, and 25%
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sustained NTA; the remaining 12% could not be clearly attributed to one of the three
categories. Only two biocontrol agents released between 1991 and 2016 caused sustained
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NTA. Hinz et al. [4] found that accurately predicting the possibility for NTA is largely a
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function of whether or not the nontarget plant species was included in pre-release testing. Of all releases made through 2016, we found only five cases (<1%) of NTA where the impacted
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plant species had been tested pre-release and was deemed not at risk. All five biocontrol agents were released in the 1980s and 1990s. For three of the five cases, insufficient testing
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methods (little replication, low number of agent specimens used, and testing limited to choice-tests) were the reasons for the false negative results.
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Despite the high accuracy with which host-specificity testing pre-release can predict the probability for direct NTA post-release, the low number of NTA cases reported (124/1623 releases), and the low number of severe direct nontarget effect cases reported (3), criticism of the practice persists. Opponents of biological control perceive the entire practice as risky, mostly because of the irreversibility of the action taken [58]. The aphorism that absence of evidence is not evidence of absence has been quoted repeatedly in the context of potentially
undiscovered NTA [e.g. 2, 3]. The argument here is that systematic and thorough post-release monitoring for NTA is rarely conducted, and that many more cases of nontarget effects would be found if the matter was more thoroughly assessed. In contrast, biological control practitioners argue that severe NTA, especially on cultivated plants and those of environmental concern, are unlikely to be overlooked [4, 10, 59]. It has become routine practice to invoke the precautionary principle when an action could potentially negatively impact the environment. The precautionary principle states that if an
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action, such as a biocontrol release, has even a very small suspected risk of causing disastrous harm to the environment, the burden of proof that it is not harmful is shifted onto those taking the action [60]. However, invoking the precautionary principle in environmental and human
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health questions regarding risk assessment is considered problematic in epistemology because of its poor and contradicting definitions and inconsistent application in conflicts [60, 61]. For
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example, while the introduction of biocontrol agents is feared by some to potentially have
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unacceptably harmful consequences for the environment, the use of pesticides to control pest species is not (because of its reversibility), despite research suggesting potential devastating
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effects on fauna and human health [62, 63]. Both opponents and proponents agree on the importance of post-release monitoring focusing on the most important nontarget species
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identified by pre-release host-specificity testing for all biocontrol projects.
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Conclusions and proposed research directions The level of effectiveness of weed biocontrol ranges from complete control (e.g. Azolla filiculoides Lam. in South Africa) to complete failure (e.g. Lantana camara L. in India) with numerous intermediate cases [57]. An important area in need of further investigation is to better understand the underlying reasons for spatial or temporal variability of biocontrol success. This could be addressed through post-release monitoring over multiple years across
environmental gradients and in different habitats. The latter has been proposed by Hoffmann et al. [7], and data are currently being compiled for all targeted weed species in South Africa. Similarly, the ‘Standardized Impact Monitoring Protocol (SIMP)’, a citizen-science weed biocontrol assessment program originally developed for the state of Idaho, USA, is intended to incorporate environmental variables across spatial scales [11]. Efforts to improve the predictability of weed biocontrol success include 1) choosing target weeds with a higher probability of successful control [64], 2) determining the most sensitive
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life stage(s) of a weed to target [e.g. 45], and 3) determining which biocontrol agent(s) will most likely be able to reduce the population growth of the target weed [e.g. 65]. However, Pichancourt et al. [66] cautioned against demographic generalizations at the weed species
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scale due to high site-year variation. Unfortunately, a recent analysis of biocontrol agent traits
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associated with effectiveness is lacking, though forthcoming. Any of the above topics may enhance biocontrol project outcomes and thus, should be integrated in project planning
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whenever possible.
With respect to environmental safety, we believe that biocontrol of weeds has garnered a
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strong record in recent decades. This is due to scientists in the discipline being very conscious of the potential of negative direct and indirect effects, the existence of tightened introduction
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regulations in many countries, and advances in pre-release host-specificity testing methodologies. For example, Paynter et al [52] highlight newly recognized risks and Müller-
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Schärer et al. [67] emphasize the need to predict potential evolutionary changes in the biocontrol agent and suggest a novel ‘real-time’ approach to studying these. Developing an overarching ecological theory of biological control, as suggested by McEvoy [25], would be the next logical and important step to transform the details of case studies into more powerful abstractions, and to develop mechanistic explanations for biocontrol success.
Declaration of interest: none Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements CABI is an international intergovernmental organisation, and we gratefully acknowledge the core financial support from our member countries (and lead agencies) including the United
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Kingdom (Department for International Development), China (Chinese Ministry of Agriculture), Australia (Australian Centre for International Agricultural Research), Canada (Agriculture and Agri-Food Canada), Netherlands (Directorate-General for International
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Cooperation), and Switzerland (Swiss Agency for Development and Cooperation). See
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http://www.cabi.org/about-cabi/who-we-work-with/key-donors/ for full details.
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plants in South Africa: an update from the southern African Plant Invaders Atlas. Bothalia 2017, 47: a2172. [51]
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native biocontrol weevil, Larinus planus, and other emerging threats on populations of the federally threatened Pitcher´s thistle, Cirsium pitcher. Biol Conserv 2012, 155: 202–211.
[57]
Winston RL, Schwarzländer M, Hinz HL, Day MD, Cock MJW, Julien MH (Eds):
Biological Control of Weeds: A World Catalogue of Agents and Their Target Weeds. Based on FHTET-2014-04, USDA Forest Service, Forest Health Technology Enterprise
Team. Available online at https://www.ibiocontrol.org/catalog/ (Accessed 20 August 2019). This online catalogue is freely available and includes the most up-to-date information on the establishment, abundance, and impact of intentional releases and the unintentional spread of weed biological control agents worldwide. [58]
Van Driesche R, Simberloff D, Blossey B, Causton C, Hoddle M, Marks C, Heinz K,
Wagner D, Warner K (Eds): Integrating Biological Control into Conservation Practice.
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Wiley Blackwell; 2016. Blossey B, Dávalos A, Simmons W, Ding J: A proposal to use plant demographic
data to assess potential weed biological control agents impacts on non-target plant
Kabat GC (Ed): Getting risk right: understanding the science of elusive health risks.
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Van den Belt H: Debating the precautionary principle: “guilty until proven
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carcinogenic risks to humans: Some organophosphate insecticides and herbicides Volume 112. Distributed by WHO Press, World Health Organization Geneva; 2017.
[64]
Paynter Q, Overton JMcC, Hill RL, Bellgard SE, Dawson MI: Plant traits predict
the success of weed biocontrol. J Appl Ecol 2012, 49: 1140–1148.
[65]
Davis AS, Landis DA, Nuzzo V, Blossey B, Gerber E, Hinz HL: Demographic models
inform selection of biocontrol agents for garlic mustard (Allaria petiolata). Ecol Appl 2006, 16, 2399–2410. [66]
Pichancourt J-B, van Klinken RD, Raghu S: Understanding the limits to species-
wide demographic generalizations: the ecology and management of Parkinsonia aculeata. Ecosphere 2019, 10: e02746. [67]
Müller-Schärer H, Bouchemousse S, Litto M, McEvoy PB, Roderick GK, Sun Y:
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Included in Box 1:
[68] Albright MF, Harman WN, Fickbohm SS, Meehan H, Groff S, Austin T: Recovery of
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native flora and behavioural responses by Galerucella spp. following biocontrol
Included in Table 1:
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[69] Zimmermann HG, Moran VC, Hoffmann JH: The renowned cactus moth, Cactoblastic cactorum: its natural history and threat to native Opuntia floras in Mexico and the
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growth of North American Opuntia. Biol Inv 2012, 14: 2355–2367.
Box 1: Three categories of nontarget attack (NTA), as defined by Hinz et al. 2019 Collateral NTA: nontarget feeding following outbreaks of released biocontrol agents and subsequent depletion of target weed populations. Collateral damage typically occurs on plant species growing in close proximity to the target weed, or within dispersal distance of the biocontrol agent, but unrelated to the targeted weed taxon. As such, the affected species are typically not tested prior to the release of the agent, and NTA is typically not predictable. Because the biocontrol agents cannot develop on these unrelated plant species, collateral
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damage lacks persistence and is always short-lived (a few days to a couple of weeks).
Collateral damage is therefore unlikely to cause noteworthy negative effects to nontarget
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plant species. For a typical example see [68].
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Spillover NTA: also occurs at high biocontrol agent densities and on nontarget plant species growing in proximity to the target weed or within dispersal distance of the biocontrol agent.
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Unlike collateral damage, spillover NTA affects confamilial species on which the biocontrol agent can typically develop fully or to some degree. However, biocontrol agents do not
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sustain populations on the non-target plant species, and NTA does not persist in the absence of the target weed. Spillover NTA will decline if populations of both the target weed and
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biocontrol agents decline. Spillover NTA can lead to negative effects at the individual plant
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level, but has thus far not been recorded to lead to negative consequences at the population level of non-target species. However, only few studies have investigated population level effects of spillover. For a typical example see [5].
Sustained NTA: occurs when the biocontrol agent is able to fully develop and sustain populations on the nontarget plant species, regardless of the presence or absence of the target
weed. In other words, the non-target plant species can serve as an alternative (albeit often suboptimal) host for the biological control agent. Similar to spillover NTA, sustained NTA affects confamilial nontarget species. Of all three NTA categories, sustained attack is the most likely to lead to negative effects at the population level and to persist independent of the
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ro of
target plant (see Table 1).
Figure 1
Percentage of intentionally introduced weed biological control agents causing
35 30 25 20 15
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10 5
n
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na
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U
nk no w
on e N
ig ht Sl
H
Va ria bl e M ed iu m
0
ea vy
Percentage of agent species
various levels of target weed control. Data from Winston et al. [57].
Figure 2
Percentage of (a) intentionally released weed biological control agents and (b)
agent releases causing non-target attack (NTA) during four different time periods. Numbers on top of bars are the number of agent species or releases causing NTA / total number of agent species released or total number of releases. Updated from Hinz et al. [4].
14/76
25
28/197
18/182
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20 15
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10 5 0
25
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(b) 35/236
59/750
2/98
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20
28/539
15 10
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Percentage of releases with NTA
2/38
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Percentage of agent species with NTA
(a)
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5
16 20
09
-2 0
08 -2 0 91 19
61 19
un
til
19
-1 9
60
90
0
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f
Table 1 Cases of weed biocontrol agents that potentially cause population level effects on nontarget plant species (as discussed in Hinz et al. 2019) Area affected
Rhinocyllus conicus
Intentional
North America
(Frölich)
introduction in 1968
Pr
(Coleoptera: Curculionidae)
Accidental
(Olivier) (= L.
introduction in the
planus) (Fabricius)
1960s, followed by
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Curculionidae)
USA, but also
active re-distribution
Predicted impact
References
20+ native Cirsium spp.;
Reduce population
54-56
C. pitcheri (Torr. ex Eaton)
growth rate and time to
Torr. & A. Gray;
extinction
C. canescens Nutt.
Several native Cirsium spp.;
Reduce population
possibly in
Cirsium pitcheri (Torr. ex
growth rate and time to
Canada
Eaton) Torr. & A. Gray
extinction
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Larinus carlinae
(Coleoptera:
Nontarget species
pr
Introduction history
e-
Agent species
54-56
Naturally or via plant
South-eastern
Native Opuntia spp.; Opuntia
cactorum (Berg).
nursery trade from the
USA
spinosissima (Martyn) Mill.
(Lepidoptera:
Dominican Republic
Pyralidae)
to Florida
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na l
Pr
e-
pr
oo
f
Cactoblastis
Elimination of populations, population reductions, attack of cultivated species
69 but see 70
PII:
S2214-5745(20)30009-2
DOI:
https://doi.org/10.1016/j.cois.2019.11.006
Reference:
COIS 654
To appear in:
Current Opinion in Insect Science
¨ Please cite this article as: Hinz HL, Winston RL, Schwarzlander M, A global review of target impact and direct nontarget effects of classical weed biological control, Current Opinion in Insect Science (2020), doi: https://doi.org/10.1016/j.cois.2019.11.006
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.
A global review of target impact and direct nontarget effects of classical weed biological control
Hariet L. Hinz1*, Rachel L. Winston2, and Mark Schwarzländer3
CABI, Rue des Grillons 1, 2800 Delémont, Switzerland
2
MIA Consulting, Shelley, ID 83274, USA
3
Department of Entomology, Plant Pathology and Nematology, University of Idaho, Moscow,
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1
ID 83844-2339, USA
*
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Corresponding author: Hariet L. Hinz, [email protected], ORCID ID: 000-0003-2930-6807
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Highlights
~1/4 weed biocontrol projects resulted in complete control
Measures of biocontrol success should be context specific
Direct nontarget attack (NTA) incidence and severity are decreasing over time
Pre-release testing predictions for NTA are more than 99% accurate
Post-release monitoring should be quantitative, targeted, and long-term
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Abstract
Recent reviews show that classical weed biocontrol can be successful in reducing the negative impacts of invasive plant species, have impressive returns on investment, and contribute to slower rates of weed spread. Quantitative post-release monitoring is necessary to account for differences in biocontrol outcomes across spatial and temporal scales. Direct
nontarget attack (NTA) incidence and severity are decreasing over time, and pre-release hostspecificity tests can accurately predict NTA post-release, as long as the nontarget plant species are included in testing. Less than 1% of NTA was found where the impacted plant species had been tested pre-release and was deemed not at risk. Effectiveness and environmental safety will likely further improve with the incorporation of new technologies, such as experimental evolutionary studies.
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Introductions
Two questions central to the discipline of classical biological control of weeds have been
debated for some time. These are a) whether the practice provides measurable successes in
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controlling target plants [1, 2] and b) whether it is environmentally safe [3, 4]. In contrast,
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there is consensus on the untenable lack of quantitative post-release monitoring data [2, 4]. However, in recent years, progress has been made to fill this gap in regions that are most
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invested in weed biocontrol [5, 6, 7, 8, 9, 10, 11]. Advancements in molecular technologies, such as techniques to identify cryptic species [e.g. 12] and genetic diversity in
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the weed system [13] or the use of molecular phylogenies to develop test plant lists and interpret results of host-specificity tests [14], are now routinely incorporated in biocontrol
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projects, which improves the probability of their success and the predictability of their safety. Other novel experimental approaches are currently being explored, for instance, behavioural
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ecology coupled with electro-physiological studies to predict host choice of biocontrol agents [15], or investigations on rapid evolutionary changes [16]. Our objectives here are to summarize recent reviews regarding the effectiveness and safety record of classical biological weed control, to synthesize the most important findings, and to outline continuing challenges. We conclude with an outline of future research directions to further advance biological weed control.
Effectiveness of biological control of weeds Several studies evaluating biological weed control outcomes used the definitions provided by Hoffmann [17], who distinguishes a) complete control, where no other control methods are needed to supress the weed, b) substantial control, where other control measures can be substantially reduced, and c) negligible control [18, 19, 20, 21]. Data used in these studies were derived from published literature but typically also included expert opinion. According to these evaluations, approximately 25% of biocontrol projects have achieved complete
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control, and 50–70% of biocontrol projects have achieved at least substantial control,
depending on the country and/or region where outcomes were assessed. In New Zealand, at least partial control was achieved for 47% of weed biocontrol projects [22].
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Schwarzländer et al. [1], who used Winston et al. [23] as the basis for their assessment,
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applied similar success criteria, but also estimated the success of each intentionally released biological control agent as well as of each individual release (taking into account that most
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biocontrol agents were released in different countries/regions, at various times, and against different target weeds). The latter, in particular, helped expose potential reasons for the
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success or failure of an agent in controlling a specific target weed in a specific region or country of release [23]. Success rates were similar for agent species and individual releases,
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with approximately 50% of both resulting in some level of control (variable, medium, or heavy impact; for definitions see Schwarzländer et al. [1]) and approximately 25% resulting
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in heavy impact (Fig. 1); 66% of weeds targeted experienced at least some level of control [1].
These measures of success have been criticized for being subjective and qualitative in nature, and because they are lacking benchmarks or controls to which biocontrol outcome data could be compared [2, 24, 25]. Benchmarks can be obtained by monitoring several pre-selected field sites prior to release of the biocontrol agent [e.g. 26], and control plots can be
established when planning agent releases. However, because some agents disperse rapidly, keeping control plots free from attack can be difficult [27]. Insecticides or fungicides have been used successfully to this end [8, 28, 29], but they also alter the control plot ecosystem by eliminating nontarget insects and/or soil fungi [30] and may have direct effects on the target weed [31]. Exclosure studies and other set design experiments do establish cause and effect relationships and can provide valuable insights into mechanisms of successful weed management and interactions of herbivory with other biotic factors, but they are often limited
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in duration and spatial scale (one or a few sites) [e.g. 5, 8, 32]. Results, therefore, cannot necessarily be extrapolated to the landscape or regional scale, at which biocontrol acts.
Alternatively, long-term (>5 years) post-release monitoring studies over large spatial scales,
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even when lacking control sites, can estimate effects of biocontrol agents on weed population growth rates while taking into account stochastic events and spatial and temporal variability
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of biocontrol success [e.g. 9, 11, 33, 34, 35, 36]. Weed and Schwarzländer [36] used a
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discrete model of the population dynamics for Dalmatian toadflax, Linaria dalmatica (L.) Mill., and found that ramet density of the plant was negatively affected by stem density in the
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prior year and abundance of the weed biocontrol agent Mecinus janthiniformis Toševski & Caldara, and positively affected by precipitation.
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In a recent extension of the criteria originally suggested by Hoffmann [17], Hoffmann et al. [7] proposed documenting outcomes of biological weed control at the population level
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through quantification of four different invasion parameters: 1) weed density, 2) area occupied, 3) biomass of the weed, and 4) number of propagules. The authors emphasized the context-specific nature of weed biocontrol and proposed recording outcomes in different regions and for different habitats (e.g. drylands, riparian). Other measures of success use economic and ecological benefits accrued by biocontrol. Economic benefits have traditionally been expressed as cost:benefit ratios. These have varied
from 2.3–4,000 for various weed systems [37, 38]. In Australia, for example, every dollar invested in weed biocontrol projects provided average benefits of $23.10 [39]. If the overall costs of a weed are high, economic benefits of weed biocontrol projects (cost:benefit ratios >1) are readily achieved, even at very modest levels of control, because costs for biocontrol tend to be low compared to other control methods [40]. Similarly, biocontrol success has also been measured based on the reduction in the target weeds’ impact. Hill and Coetzee [6] used the generic impact scoring system (GISS) proposed by Nentwig et al. [41] to assess the
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impact of eight water weeds in South Africa before and after biological control. The introduction of biocontrol agents drastically reduced the environmental and socio-economic impact scores for four of the five most serious exotic aquatic weeds [6].
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It has also been proposed that success of biocontrol projects should be measured as a
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decrease in the finite population growth rate (lambda) of the target weed or in its equilibrium population size using demographic modelling [2, 42, 43]. This has rarely been done in weed
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biocontrol [but see 5, 32, 44, 45]. For some invasive trees and shrubs, it has been shown that seed-feeding biocontrol agents would need to destroy close to 100% of seeds to reduce
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lambda to <1 [46]. Nonetheless, biocontrol agents that reduced seed production of several invasive Acacia shrubs and trees by less than 100% still contributed to successful control by
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making manual and chemical control strategies economically viable [47]. Even if weed biocontrol agents do not reduce weed stand densities, they can still slow rates of spread and
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curb range expansion of invasive plant populations [48, 49]. For example, an analysis of the Southern African Plant Invaders Atlas, which documents alien plants growing outside of cultivation since 1994, found that although the number of quarter-degree squares occupied by alien plants increased by approximately 50% between 2000 and 2016, classical biological control programs reduced the rate of spread of some taxa and, in a few cases, led to range contractions, while other interventions (mechanical, chemical) had no detectable effect [50].
Environmental safety of biological control of weeds In the following, we focus on direct NTA because indirect effects, regardless of whether detrimental or beneficial, are difficult to predict and have thus far rarely been assessed for weed biological control [51, 52]. The extent of direct NTA caused by biological control agents varies substantially with outcomes ranging from negligible to negative effects at the population level. In a recent review, Suckling and Sforza [53] accounted for the magnitude of NTA by proposing a scale
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from ‘minimal’ to ‘massive’, covering effects impairing nontarget plant individuals,
populations, communities, and ecosystem processes. Alternatively, Hinz et al. [4] used
persistence of NTA in their review as the main criterion assessing its severity. They defined
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three categories: ‘collateral’, ‘spillover’, and ‘sustained’ direct NTA (Box 1). Using this
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categorization, the authors concluded that only sustained direct NTA is likely to lead to population-level effects [4]. Blossey [42] argued that nontarget effects should only include
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cases where the finite growth rate (lambda) of a nontarget population has been supressed to <1 as the result of successful establishment of a biological control agent. This would,
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however, require that demographic modelling data exist for the nontarget plant species, which is rarely the case [but see 54, 55, 56], because the laborious and difficult process of collecting
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demographic modelling data has already limited these studies for target weed species.
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Suckling and Sforza [53] and Hinz et al. [4] both found that, based on available data, less than 1% of all classical weed biocontrol agent releases to date have the potential to lead to negative population-level nontarget effects. The three most severe cases identified in both reviews are listed in Table 1. All three biocontrol agents have in common that their releases occurred in the 1950s and 1960s when release protocols for weed biocontrol agents did not consider the risk to native species.
In their review, Hinz et al. [4] used releases made through 2008. Utilizing the more recently updated Winston et al. [57], we report herein data for releases made through 2016, as this was the most recent release known to have resulted in NTA. Of 493 agents intentionally released through 2016, 62 (12.6%) have been recorded attacking nontarget species in the field, two more than in the recent review by Hinz et al. [4]. Of 1,623 releases made using the 493 agent species, 124 (7.6%) resulted in NTA. Both the proportions of agent species and releases with NTA have declined over time (Fig. 2). This either suggests that methods to
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determine the environmental safety of weed biocontrol agents have improved over time, or that regulations to import agents have become stricter, or a combination of both. Overall, intentionally released biocontrol agents caused 12% collateral, 51% spillover, and 25%
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sustained NTA; the remaining 12% could not be clearly attributed to one of the three
categories. Only two biocontrol agents released between 1991 and 2016 caused sustained
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NTA. Hinz et al. [4] found that accurately predicting the possibility for NTA is largely a
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function of whether or not the nontarget plant species was included in pre-release testing. Of all releases made through 2016, we found only five cases (<1%) of NTA where the impacted
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plant species had been tested pre-release and was deemed not at risk. All five biocontrol agents were released in the 1980s and 1990s. For three of the five cases, insufficient testing
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methods (little replication, low number of agent specimens used, and testing limited to choice-tests) were the reasons for the false negative results.
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Despite the high accuracy with which host-specificity testing pre-release can predict the probability for direct NTA post-release, the low number of NTA cases reported (124/1623 releases), and the low number of severe direct nontarget effect cases reported (3), criticism of the practice persists. Opponents of biological control perceive the entire practice as risky, mostly because of the irreversibility of the action taken [58]. The aphorism that absence of evidence is not evidence of absence has been quoted repeatedly in the context of potentially
undiscovered NTA [e.g. 2, 3]. The argument here is that systematic and thorough post-release monitoring for NTA is rarely conducted, and that many more cases of nontarget effects would be found if the matter was more thoroughly assessed. In contrast, biological control practitioners argue that severe NTA, especially on cultivated plants and those of environmental concern, are unlikely to be overlooked [4, 10, 59]. It has become routine practice to invoke the precautionary principle when an action could potentially negatively impact the environment. The precautionary principle states that if an
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action, such as a biocontrol release, has even a very small suspected risk of causing disastrous harm to the environment, the burden of proof that it is not harmful is shifted onto those taking the action [60]. However, invoking the precautionary principle in environmental and human
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health questions regarding risk assessment is considered problematic in epistemology because of its poor and contradicting definitions and inconsistent application in conflicts [60, 61]. For
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example, while the introduction of biocontrol agents is feared by some to potentially have
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unacceptably harmful consequences for the environment, the use of pesticides to control pest species is not (because of its reversibility), despite research suggesting potential devastating
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effects on fauna and human health [62, 63]. Both opponents and proponents agree on the importance of post-release monitoring focusing on the most important nontarget species
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identified by pre-release host-specificity testing for all biocontrol projects.
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Conclusions and proposed research directions The level of effectiveness of weed biocontrol ranges from complete control (e.g. Azolla filiculoides Lam. in South Africa) to complete failure (e.g. Lantana camara L. in India) with numerous intermediate cases [57]. An important area in need of further investigation is to better understand the underlying reasons for spatial or temporal variability of biocontrol success. This could be addressed through post-release monitoring over multiple years across
environmental gradients and in different habitats. The latter has been proposed by Hoffmann et al. [7], and data are currently being compiled for all targeted weed species in South Africa. Similarly, the ‘Standardized Impact Monitoring Protocol (SIMP)’, a citizen-science weed biocontrol assessment program originally developed for the state of Idaho, USA, is intended to incorporate environmental variables across spatial scales [11]. Efforts to improve the predictability of weed biocontrol success include 1) choosing target weeds with a higher probability of successful control [64], 2) determining the most sensitive
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life stage(s) of a weed to target [e.g. 45], and 3) determining which biocontrol agent(s) will most likely be able to reduce the population growth of the target weed [e.g. 65]. However, Pichancourt et al. [66] cautioned against demographic generalizations at the weed species
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scale due to high site-year variation. Unfortunately, a recent analysis of biocontrol agent traits
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associated with effectiveness is lacking, though forthcoming. Any of the above topics may enhance biocontrol project outcomes and thus, should be integrated in project planning
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whenever possible.
With respect to environmental safety, we believe that biocontrol of weeds has garnered a
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strong record in recent decades. This is due to scientists in the discipline being very conscious of the potential of negative direct and indirect effects, the existence of tightened introduction
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regulations in many countries, and advances in pre-release host-specificity testing methodologies. For example, Paynter et al [52] highlight newly recognized risks and Müller-
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Schärer et al. [67] emphasize the need to predict potential evolutionary changes in the biocontrol agent and suggest a novel ‘real-time’ approach to studying these. Developing an overarching ecological theory of biological control, as suggested by McEvoy [25], would be the next logical and important step to transform the details of case studies into more powerful abstractions, and to develop mechanistic explanations for biocontrol success.
Declaration of interest: none Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements CABI is an international intergovernmental organisation, and we gratefully acknowledge the core financial support from our member countries (and lead agencies) including the United
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Kingdom (Department for International Development), China (Chinese Ministry of Agriculture), Australia (Australian Centre for International Agricultural Research), Canada (Agriculture and Agri-Food Canada), Netherlands (Directorate-General for International
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Cooperation), and Switzerland (Swiss Agency for Development and Cooperation). See
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http://www.cabi.org/about-cabi/who-we-work-with/key-donors/ for full details.
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Box 1: Three categories of nontarget attack (NTA), as defined by Hinz et al. 2019 Collateral NTA: nontarget feeding following outbreaks of released biocontrol agents and subsequent depletion of target weed populations. Collateral damage typically occurs on plant species growing in close proximity to the target weed, or within dispersal distance of the biocontrol agent, but unrelated to the targeted weed taxon. As such, the affected species are typically not tested prior to the release of the agent, and NTA is typically not predictable. Because the biocontrol agents cannot develop on these unrelated plant species, collateral
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damage lacks persistence and is always short-lived (a few days to a couple of weeks).
Collateral damage is therefore unlikely to cause noteworthy negative effects to nontarget
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plant species. For a typical example see [68].
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Spillover NTA: also occurs at high biocontrol agent densities and on nontarget plant species growing in proximity to the target weed or within dispersal distance of the biocontrol agent.
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Unlike collateral damage, spillover NTA affects confamilial species on which the biocontrol agent can typically develop fully or to some degree. However, biocontrol agents do not
na
sustain populations on the non-target plant species, and NTA does not persist in the absence of the target weed. Spillover NTA will decline if populations of both the target weed and
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biocontrol agents decline. Spillover NTA can lead to negative effects at the individual plant
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level, but has thus far not been recorded to lead to negative consequences at the population level of non-target species. However, only few studies have investigated population level effects of spillover. For a typical example see [5].
Sustained NTA: occurs when the biocontrol agent is able to fully develop and sustain populations on the nontarget plant species, regardless of the presence or absence of the target
weed. In other words, the non-target plant species can serve as an alternative (albeit often suboptimal) host for the biological control agent. Similar to spillover NTA, sustained NTA affects confamilial nontarget species. Of all three NTA categories, sustained attack is the most likely to lead to negative effects at the population level and to persist independent of the
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ro of
target plant (see Table 1).
Figure 1
Percentage of intentionally introduced weed biological control agents causing
35 30 25 20 15
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10 5
n
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na
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U
nk no w
on e N
ig ht Sl
H
Va ria bl e M ed iu m
0
ea vy
Percentage of agent species
various levels of target weed control. Data from Winston et al. [57].
Figure 2
Percentage of (a) intentionally released weed biological control agents and (b)
agent releases causing non-target attack (NTA) during four different time periods. Numbers on top of bars are the number of agent species or releases causing NTA / total number of agent species released or total number of releases. Updated from Hinz et al. [4].
14/76
25
28/197
18/182
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20 15
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10 5 0
25
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(b) 35/236
59/750
2/98
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20
28/539
15 10
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Percentage of releases with NTA
2/38
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Percentage of agent species with NTA
(a)
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5
16 20
09
-2 0
08 -2 0 91 19
61 19
un
til
19
-1 9
60
90
0
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Table 1 Cases of weed biocontrol agents that potentially cause population level effects on nontarget plant species (as discussed in Hinz et al. 2019) Area affected
Rhinocyllus conicus
Intentional
North America
(Frölich)
introduction in 1968
Pr
(Coleoptera: Curculionidae)
Accidental
(Olivier) (= L.
introduction in the
planus) (Fabricius)
1960s, followed by
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Curculionidae)
USA, but also
active re-distribution
Predicted impact
References
20+ native Cirsium spp.;
Reduce population
54-56
C. pitcheri (Torr. ex Eaton)
growth rate and time to
Torr. & A. Gray;
extinction
C. canescens Nutt.
Several native Cirsium spp.;
Reduce population
possibly in
Cirsium pitcheri (Torr. ex
growth rate and time to
Canada
Eaton) Torr. & A. Gray
extinction
na l
Larinus carlinae
(Coleoptera:
Nontarget species
pr
Introduction history
e-
Agent species
54-56
Naturally or via plant
South-eastern
Native Opuntia spp.; Opuntia
cactorum (Berg).
nursery trade from the
USA
spinosissima (Martyn) Mill.
(Lepidoptera:
Dominican Republic
Pyralidae)
to Florida
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na l
Pr
e-
pr
oo
f
Cactoblastis
Elimination of populations, population reductions, attack of cultivated species
69 but see 70