Taxonomic uncertainty in pest risks or modelling artefacts? Implications for biosecurity policy and practice

Kriticos, Darren J.; Morin, L.; Webber, Bruce L.

doi:10.3897/neobiota.23.7496

Cited by 8 publications

(20 citation statements)

References 43 publications

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“…However, the appropriate background for testing realized niche shifts between native‐range source clades and destinations is less clear. One could argue that background environments should only include areas that have been accessible to each clade in its native range (Barve et al ), and that it is inappropriate to change the occurrence points (native clades vs entire native range) without also changing the spatial extent of the background (Kriticos et al ). On the other hand, changing the background extent confounds the influence of using different occurrence records.…”

Section: Methodsmentioning

confidence: 99%

Patterns of niche filling and expansion across the invaded ranges of an Australian lizard

et al. 2015

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Studies of realized niche shifts in alien species typically ignore the potential effects of intraspecific niche variation and different invaded‐range environments on niche lability. We incorporate our detailed knowledge of the native‐range source populations and global introduction history of the delicate skink Lampropholis delicata to examine intraspecific variation in realized niche expansion and unfilling, and investigate how alternative niche modelling approaches are affected by that variation. We analyzed the realized niche dynamics of L. delicata using an ordination method, ecological niche models (ENMs), and occurrence records from 1) Australia (native range), 2) New Zealand, 3) Hawaii, 4) the two distinct native‐range clades that were the sources for the New Zealand and Hawaii introductions, and 5) the species’ global range (including Lord Howe Island, Australia). We found a gradient of realized niche change across the invaded ranges of L. delicata: niche stasis on Lord Howe Island, niche unfilling in New Zealand (16%), and niche unfilling (87%) and expansion (14%) in Hawaii. ENMs fitted to native‐range data generally identified suitable climatic conditions at sites where the species has established non‐native populations, whereas ENMs based on native‐range source clades and non‐native populations had lower spatial transferability. Our results suggest that the extent to which realized niches are maintained during invasion does not depend on species‐level traits. When realized niche shifts are predominately due to niche unfilling, fully capturing species’ responses along climatic gradients by basing ENMs on native distributions may be more important for accurate invasion forecasts than incorporating phylogenetic differentiation, or integrating niche changes in the invaded range.

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Section: Methodsmentioning

confidence: 99%

Patterns of niche filling and expansion across the invaded ranges of an Australian lizard

et al. 2015

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“…In Maxent, variable importance is estimated in two ways -one during model building and the other on permutation tests on the final model. Kriticos et al (2014) focus on the second and expect similar covariate rankings across all 5 datasets. We agree that repeated random samples of the full distribution of a species are likely to lead to similar covariate rankings, provided there are enough samples to reliably model the species and provided the entity is in fact a single species.…”

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confidence: 94%

“…We used the modelling software Maxent Dudik 2008) and 7 covariates selected for their likely ecological relevance to model these five datasets. Kriticos et al (2014) note that the covariate rankings in the five models vary, which they interpret as 'unstable'. They state "instability in the covariate importance rankings in this type of analysis provides an indication that the model may be unsound".…”

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Response to Kriticos et al.

Elith¹,

Burgman²

2014

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Citation: Elith J, Burgman MA (2014) Response to Kriticos et al. (2014) discuss a recent paper of ours (Elith et al. 2013). While we agree with several of the points they raise, in this brief response we focus on clarifying a subset of issues around improving pest risk modelling. We do so because several of their suggestions are based on misunderstandings of technical details and will not, as they hope, lead to improved modelling practice. Elith et al. (2013) used the Puccinia psidii complex as a case study to explore the impact of taxonomic uncertainty on modelled predictions. The work was clear in stating that it did not intend to provide definitive predictions and advice for biosecurity managers. This position is clear in the title and in statements in Elith et al. (2013) such as 'The purpose of this study is to explore the implications of taxonomic uncertainty for the management of a new invasive pathogen. We use the Australian incursion of myrtle/ guava rust as an example, not to argue which taxonomic interpretation, data set or model is correct, but to highlight the impact of taxonomic belief on modelled predictions.' We discussed how to make risk weighted decisions that accommodate this kind of uncertainty. We created 5 datasets of species records that were either the full set of available presence records for the P. psidii complex ("Pucc94") or subsets of that, each of which accorded with a different taxonomic interpretation.The Kriticos et al. (2014) commentary primarily uses for illustration the Pucc94 dataset (94 records) and the Ured27 dataset -a subset of Pucc94 comprising 10 records of Uredo rangelii (variously viewed as a separate species or a member of the complex) and an additional 17 records from similar environments (see Elith et al. 2013 for details). Elith et al. (2013) emphasised that "we recognise that the basis for Copyright J. Elith, M.A. Burgman. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.NeoBiota 23: 95-99 (2014)

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“…One popular example is MaxEnt, which uses distribution data in combination with derived background observations (Phillips et al 2006). However, MaxEnt and other species distribution models may not extrapolate reliably especially into novel climates (Elith and Leathwick 2009;Elith et al 2012;Kriticos et al 2014). An alternative is CLIMEX-Compare Locations (Sutherst and Maywald 1985), which uses literature and distribution data to fit the model parameters.…”

Section: Introductionmentioning

confidence: 99%

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

Hong¹,

Magarey²,

Borchert³

et al. 2015

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Citation: Hong SC, Magarey RD, Borchert DM, Vargas RI, Souder SK (2015) Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly). NeoBiota 27: 37-67. doi: 10.3897/neobiota.27.5177 Abstract This study introduces a simple generic model, the Generic Pest Forecast System (GPFS), for simulating the relative populations of non-indigenous arthropod pests in space and time. The model was designed to calculate the population index or relative population using hourly weather data as influenced by developmental rate, high and low temperature mortalities and wet soil moisture mortality. Each module contains biological parameters derived from controlled experiments. The hourly weather data used for the model inputs were obtained from the National Center of Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) at a 38 km spatial resolution. A combination of spatial and site-specific temporal data was used to validate the GPFS models. The oriental fruit fly, Bactrocera dorsalis (Hendel), was selected as a case study for this research because it is climatically driven and a major pest of fruit production. Results from the GPFS model were compared with field B. dorsalis survey data in three locations: 1) Bangalore, India; 2) Hawaii, USA; and 3) Wuhan, China. The GPFS captured the initial outbreaks and major population peaks of B. dorsalis reasonably well, although agreement varied between sites. NeoBiota 27: 37-67 (2015) doi: 10.3897/neobiota.27.5177 http://neobiota.pensoft.net Seung Cheon Hong et al. / NeoBiota 27: 37-67 (2015) 38 the highest match between the observed and simulated B. dorsalis populations, with indices of agreement of 0.85. The site-specific temporal comparisons implied that the GPFS model is informative for prediction of relative abundance. Spatial results from the GPFS model were also compared with 161 published observations of B. dorsalis distribution, mostly from East Asia. Since parameters for pupal overwintering and survival were unknown from the literature, these were inferred from the distribution data. The study showed that GPFS has promise for estimating suitable areas for B. dorsalis establishment and potentially other non-indigenous pests. It is concluded that calibrating prediction models with both spatial and sitespecific temporal data may provide more robust and reliable results than validations with either data set alone. RESEARCH ARTICLE Advancing research on alien species and biological invasions A peer-reviewed open-access journal NeoBiota

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Taxonomic uncertainty in pest risks or modelling artefacts? Implications for biosecurity policy and practice

Cited by 8 publications

References 43 publications

Patterns of niche filling and expansion across the invaded ranges of an Australian lizard

Patterns of niche filling and expansion across the invaded ranges of an Australian lizard

Response to Kriticos et al.

Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly)

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