The effect of data sources and quality on the predictive capacity of CLIMEX models: An assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Lawson, Ben E.; Day, Michael; Bowen, Michiala; Klinken, Rieks D. van; Zalucki, Myron P.

doi:10.1016/j.biocontrol.2009.10.001

Cited by 12 publications

(7 citation statements)

References 23 publications

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“…The constraints imposed by biotic influences in the species’ native range may be absent in exotic locations, thus allowing it to expand its range beyond its realised Hutchinsonian niche. It is important to supplement distribution data with seasonal phenology data when fitting parameters, because phenology data highlight the species’ response to climatic trends, while distributional data allow more effective fitting of stress parameters by limiting the species envelope to the observed distribution (Lawson et al. , 2010).…”

Section: Methodsmentioning

confidence: 99%

Impacts of climate change and land‐use on the potential distribution of an invasive weed: a case study of Lantana camara in Australia

2012

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Taylor S, Kumar L & Reid N (2012). Impacts of climate change and land‐use on the potential distribution of an invasive weed: a case study of Lantana camara in Australia. Weed Research.52, 391–401. Summary Lantana camara (lantana) is an extremely invasive species in many countries, including Australia. Biosecurity agencies will benefit from prior knowledge of the potential distribution of L. camara, under current and future climate scenarios. A process‐based niche model for this species was developed using the CLIMEX modelling package. The potential distribution generated from this model was refined by incorporating existing land‐use data in a Geographical Information System (GIS). The potential distribution of L. camara under current climate indicated that L. camara occupies almost the full extent of climatically suitable habitat available to it in Australia. Under future climate scenarios, L. camara range expands into new areas in Victoria, South Australia and Tasmania, while the northern parts of the continent become climatically unsuitable. This trend continued with the inclusion of land‐use data, although with a more restricted distri‐bution, as locations with suitable climate but unsuitable land‐use were excluded. Weed control authorities in the new areas at risk of invasion under climate change need to be alerted to this emerging threat, so that effective response measures can be taken.

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Section: Methodsmentioning

confidence: 99%

Impacts of climate change and land‐use on the potential distribution of an invasive weed: a case study of Lantana camara in Australia

2012

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“…Similar issues apply to CLIMEX (Box 5.2) because the model is often primarily fitted using location data. The CLIMEX predicted distribution may be closer to the realised niche than the fundamental niche, depending on the extent to which the dispersal of the species has been limited and on the amount of additional physiological data (Lawson et al, 2010). Physiological data, if reliable and if successfully rescaled to be consistent with the predictor information, should allow the prediction to edge closer to the fundamental niche (Box 5.2).…”

Section: 51mentioning

confidence: 99%

“…For instance, CLIMEX can be affected by the number of records, depending on the amount of physiological data available. Without physiological data, CLIMEX requires at least one record in each of the important combinations of environmental conditions (the axes of the environmental space defined by the predictors) inhabited by the species (Lawson et al, 2010). Geographic proximity of records is unimportant in CLIMEX, and having more than one record in a given environmental combination does not help model fitting, except to confirm that the conditions are suitable.…”

Section: Issue 2: How Species Records Affect the Predicted Distributionmentioning

confidence: 99%

Predicting Distributions of Invasive Species

Elith¹

2017

Invasive Species

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Note to reader: This chapter was primarily written in 2011 and will be published in a book,(due to be published in 2016). This can be cited according to its arXiv reference. This is the second version I have submitted to arXiv, with relatively minor changes mostly to wording. Predicting distributions of invasive speciesJane Elith School of BioSciences, The University of Melbourne 3010. Australia j.elith@unimelb.edu.au AbstractThis chapter aims to inform a practitioner about current methods for predicting potential distributions of invasive species. It mostly addresses single species models, covering the conceptual bases, touching on mechanistic models, and then focusing on methods using species distribution records and environmental data to predict distributions. The commentary in this last section is oriented towards key issues that arise in fitting, and predicting with, these models (which include CLIMEX, MaxEnt and other regression methods). In other words, it is more about the process of thinking about the data and the modelling problem (which is a challenging one) than it is about one technique versus another. The discussion helps clarify the necessary steps and expertise for predicting distributions. Some researchers are optimistic that correlative models will predict with high precision; while that may be true for some species at some scales of evaluation, I believe that the issues discussed in this chapter show that substantial errors are reasonably likely. I am hopeful that ongoing developments will produce models better suited to the task and tools to help practitioners to better understand predictions and their uncertainties.

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“…In a previous study 29 , we also used CLIMEX to assess the potential distribution of suitable habitat of CPB in Kazakhstan, southern Russia and northwest China and achieved results similar to those of MaxEnt. In this research, the selection of MaxEnt can avoid potential errors that may occur when physiological data (used in CLIMEX) is uncertain or inaccurate 30 . MaxEnt may also perform better than other correlative models when the true absence data are unavailable 31 , 32 .…”

Section: Discussionmentioning

confidence: 99%

Impact of climate and host availability on future distribution of Colorado potato beetle

Hawthorne

Qin

et al. 2017

Sci Rep

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Colorado Potato Beetle (CPB) is a devastating invasive pest of potato both in its native North America and now across Eurasia. It also damages eggplant, tomato and feeds on several wild species in the Solanaceae, such as S. eleagnifolium and S. rostratum Dunal (SR). Since first categorized as a pest in 1864, CPB has spread rapidly across North America, Europe and Asia. In light of its invasiveness and economic importance, it is necessary to study how climate change and host availability may alter the distribution of the CPB. Maximum Entropy (MaxEnt) models were used to anticipate global range expansion as influenced by environmental conditions, and by the possibility of cooperative invasion of CPB and its wild host SR. The results indicate that both CPB and SR can occupy warm areas of North America, South Africa, Europe, China, and Australia. Future climate conditions may promote CPB expansion into northern regions and SR into the circumpolar latitudes. The existing range and continued spread of SR may also assist the global expansion of CPB. Future management of this pest should consider the impacts of global climate change and host availability on its potential global distribution.

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The effect of data sources and quality on the predictive capacity of CLIMEX models: An assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Cited by 12 publications

References 23 publications

Impacts of climate change and land‐use on the potential distribution of an invasive weed: a case study of Lantana camara in Australia

Impacts of climate change and land‐use on the potential distribution of an invasive weed: a case study of Lantana camara in Australia

Predicting Distributions of Invasive Species

Impact of climate and host availability on future distribution of Colorado potato beetle

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