Sensitivity Analysis of CLIMEX Parameters in Modelling Potential Distribution of Lantana camara L.

Ecosystem Management, School of Environmental and Rural Science, University of New England, Armidale, New South Wales, Australia.
PLoS ONE (Impact Factor: 3.23). 07/2012; 7(7):e40969. DOI: 10.1371/journal.pone.0040969
Source: PubMed


A process-based niche model of L. camara L. (lantana), a highly invasive shrub species, was developed to estimate its potential distribution using CLIMEX. Model development was carried out using its native and invasive distribution and validation was carried out with the extensive Australian distribution. A good fit was observed, with 86.7% of herbarium specimens collected in Australia occurring within the suitable and highly suitable categories. A sensitivity analysis was conducted to identify the model parameters that had the most influence on lantana distribution. The changes in suitability were assessed by mapping the regions where the distribution changed with each parameter alteration. This allowed an assessment of where, within Australia, the modification of each parameter was having the most impact, particularly in terms of the suitable and highly suitable locations. The sensitivity of various parameters was also evaluated by calculating the changes in area within the suitable and highly suitable categories. The limiting low temperature (DV0), limiting high temperature (DV3) and limiting low soil moisture (SM0) showed highest sensitivity to change. The other model parameters were relatively insensitive to change. Highly sensitive parameters require extensive research and data collection to be fitted accurately in species distribution models. The results from this study can inform more cost effective development of species distribution models for lantana. Such models form an integral part of the management of invasive species and the results can be used to streamline data collection requirements for potential distribution modelling.

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Available from: Lalit Kumar, Oct 29, 2015
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    • "For example, niche model predictions may be affected by the quality of occurrence data, sampling bias, resolution of spatial data layers, species characteristics , and spatial autocorrelation (Guisan et al. 2007a,b; Taylor and Kumar 2012; Anderson 2013; Dormann et al. 2013; Syfert et al. 2013). The physiological temperature and moisture thresholds generated in laboratory studies for codling moth may not have covered the entire range of genetic and phenotypic variability in codling moth populations globally; CLIMEX parameters have uncertainties (Taylor and Kumar 2012). Max- Ent model is also affected by different decisions made during model calibration; for example, selection of background points and extent, value of RM, and selection of feature types can have immense influences on model predictions (Barve et al. 2011, Owens et al. 2013, Shcheglovitova and Anderson 2013, Boria et al. 2014). "
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    ABSTRACT: Accurate assessment of insect pest establishment risk is needed by national plant protection organizations to negotiate international trade of horticultural commodities that can potentially carry the pests and result in inadvertent introductions in the importing countries. We used mechanistic and correlative niche models to quantify and map the global patterns of the potential for establishment of codling moth ( Cydia pomonella L.), a major pest of apples, peaches, pears, and other pome and stone fruits, and a quarantine pest in countries where it currently does not occur. The mechanistic model CLIMEX was calibrated using species-specific physiological tolerance thresholds, whereas the correlative model MaxEnt used species occurrences and climatic spatial data. Projected potential distribution from both models conformed well to the current known distribution of codling moth. None of the models predicted suitable environmental conditions in countries located between 20°N and 20°S potentially because of shorter photoperiod, and lack of chilling requirement (<60 d at ≤10°C) in these areas for codling moth to break diapause. Models predicted suitable conditions in South Korea and Japan where codling moth currently does not occur but where its preferred host species (i.e., apple) is present. Average annual temperature and latitude were the main environmental variables associated with codling moth distribution at global level. The predictive models developed in this study present the global risk of establishment of codling moth, and can be used for monitoring potential introductions of codling moth in different countries and by policy makers and trade negotiators in making science-based decisions.
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    • "One major assumption that underlies such models is that climate is the primary factor defining the potential range of plants and other poikilotherms (Woodward, 1987). A range of software is now available which can be used to model species' current and future distributions (Kriticos and Randall, 2001; Hirzel and LeLay, 2008) one of which, CLIMEX, has been widely used to assess invasion risks from invasive alien species (Kriticos et al., 2011a; Chejara et al., 2010; Kriticos and Leriche, 2010; Taylor et al., 2012a, b). It is a mechanistic model (Hijmans and Graham, 2006) which is well suited for applications that involve transferability or projections of species distribution into novel environments (Randin et al., 2006), such as investigating the impacts of climate change on species' potential ranges (Kriticos et al., 2011a). "

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    • "These results contrasted with the results of the sensitivity analysis for Lantana camara L. [64], rated as one of the ten most destructive weeds in the world [65]. Taylor [64] showed that the distribution of lantana was highly sensitive to DV0, DV3 and SM0 parameter changes. Additionally, Taylor [64] showed that DV0 and DV3 changes had the substantially modified suitable and highly suitable lantana location in Australia. "
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    ABSTRACT: Using CLIMEX and the Taguchi Method, a process-based niche model was developed to estimate potential distributions of Phoenix dactylifera L. (date palm), an economically important crop in many counties. Development of the model was based on both its native and invasive distribution and validation was carried out in terms of its extensive distribution in Iran. To identify model parameters having greatest influence on distribution of date palm, a sensitivity analysis was carried out. Changes in suitability were established by mapping of regions where the estimated distribution changed with parameter alterations. This facilitated the assessment of certain areas in Iran where parameter modifications impacted the most, particularly in relation to suitable and highly suitable locations. Parameter sensitivities were also evaluated by the calculation of area changes within the suitable and highly suitable categories. The low temperature limit (DV2), high temperature limit (DV3), upper optimal temperature (SM2) and high soil moisture limit (SM3) had the greatest impact on sensitivity, while other parameters showed relatively less sensitivity or were insensitive to change. For an accurate fit in species distribution models, highly sensitive parameters require more extensive research and data collection methods. Results of this study demonstrate a more cost effective method for developing date palm distribution models, an integral element in species management, and may prove useful for streamlining requirements for data collection in potential distribution modeling for other species as well.
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