The current global distribution of L. camara taken from the Global Biodiversity Information Facility 2007. Red dots indicate occurrence records of L. camara . doi:10.1371/journal.pone.0035565.g001 

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... climate responses of lantana based on its native distribution and invasive distribution outside Australia. This model was then used to project its potential distribution under current climate, using the extensive Australian distribution data for model validation and assess the impacts of climate change on its potential distribution using two global climate models (GCM), CSIRO- Mk3.0 and MIROC-H. These were run with the A1B and A2 SRES (Special Report on Emissions Scenarios) emission scenarios for 2030 and 2070. CLIMEX for Windows Version 3 [13,34–35] was used to develop a model of the potential distribution of L. camara under current and future climate scenarios. CLIMEX is based on the observation that the distribution of plants and poikilothermal animals is primarily determined by climate [36]. The software works on the basis of an eco-physiological model that assumes that at each location, a species may experience a favourable season with positive population growth and an unfavourable season that causes population decline [35]. The user can use the model to infer parameters that describe the species’ response to climate based on its geographic range or phenological observations [35]. CLIMEX can also be used deductively to apply climate response parameters extracted from experimental observations to climatic datasets. In practice, both approaches can be applied to inform the selection of parameter values. These parameters can then be applied to novel climates to project the species’ potential range in new regions or climate scenarios [22,37]. The potential for population growth during favourable climate conditions is described by an annual growth index (GI A ) that conforms to the law of tolerance [38] and the law of minimum [39]. Four stress indices (cold, wet, hot and dry) and up to four interaction stresses (hot–dry, hot–wet, cold–dry and cold–wet) are used to describe the probability that the population can survive unfavourable conditions. The growth and stress indices are calculated weekly and combined into an overall annual index of climatic suitability, the Ecoclimatic index (EI) which is theoretically scaled from 0 to 100. Establishment is only possible if EI . 0. In practice, EI values close to the maximum are rare, and confined to species with an equatorial range, as this would imply ideal growing conditions year-round [40]. EI values close to zero indicate a low probability of conditions conducive to persistence in time and space. In such marginally suitable climates, species are likely to be restricted to favourable microhabitats, and to exhibit significant metapopulation dynamics. The genus Lantana L. (Verbenaceae) includes up to 150 species [41–42]. Many of these species are native to South America, Central America or southern North America, while a few species occur naturally in Africa and Asia [43]. There is considerable uncertainty associated with the taxonomy of the genus Lantana . Four distinct groups can be recognized within the genus [44]. These are referred to as Lantana sections Calliorheas , Sarcolippia , Rhytocamara and Camara . Lantana section Camara is divided into three complexes based on L. urticifolia , L. hirsuta and L. camara . The L. camara complex contains the weedy lantana generally referred to as L. camara L. sensu lato , which has a pan-tropical distribution [1]. Lantana camara sensu stricto is known from Jamaica, Trinidad, Mexico, Brazil and Florida [44]. It may have a wider native distribution in South America [45] extending to Argentina and Uruguay [1,46]. The present study only addresses the ‘weedy taxa’ of Lantana section Camara which are the most prevalent taxa in the genus. They are important due to economic and environmental impacts as they can invade natural and agricultural ecosystems [47–48]. Its environmental impacts are especially damaging in native forests that have undergone disturbance. In such cases, lantana forms a dense understorey, disrupts succession and decreases biodiversity [1,32]. In areas that have a high density of lantana, species richness is reduced [33,49] and local flora is threatened [50–51]. In natural systems, dense lantana infestations can alter fire regimes [52]. Lantana is a weed of important crops such as coffee, oil palms, coconuts, cotton, bananas, pineapples, sugarcane, tea, rubber and rice in various countries [53]. It forms dense thickets in pastures, outcompeting desirable pasture species and rendering infested areas useless for pasture [1,53]. Within the ‘weedy taxa’, there are many variants of L. camara , referred to here as varieties. Twenty-nine varieties are recognized in Australia [54]. The common name lantana is used in the remainder of the paper to refer to the weedy taxa of the section Camara . The Global Biodiversity Information Facility (GBIF) is a database of natural history collections around the world for various species and is available for download. Information on L. camara distribution was downloaded [55] (Figure 1) and used in parameter fitting. Some 4126 records were downloaded but many did not have geographic coordinates and were removed, leaving 2753 records. However, many of these records were duplicates and were also removed. Thus 1740 records from the GBIF database were used in parameter fitting. Distribution data from South Africa [56] and Asia [57–61] were also obtained to assist in fitting parameters. Seasonal phenology data for the southern states of Brazil were used to fit growth parameters [62,63]. Although Winder’s seasonal phenology observations were restricted to Lantana tiliaefolia and L. glutinosa , the ecology of these two species are similar to the weedy taxa of lantana, and thus these data were used in parameter fitting. The CliMond 10 9 gridded climate data [64] were used for modelling. Average minimum monthly temperature ( T min ), average maximum monthly temperature ( T max ), average monthly precipitation ( P total ) and relative humidity at 09:00 h ( RH 09:00 ) and 15:00 h ( RH 15:00 ) were used to represent historical climate (averaging period 1950–2000). The same five variables were used to characterize potential future climate in 2030 and 2070, based on two Global Climate Models (GCMs), CSIRO-Mk3.0 [65] and MIROC-H (Centre for Climate Research, Japan) with the A1B and A2 SRES scenarios [66]. These were available as part of the CliMond dataset. The two GCMs were selected from 23 GCMs for the CliMond dataset based on three criteria [64]: 1. The temperature, precipitation, mean sea level pressure and specific humidity variables required for CLIMEX were available for these two GCMs. 2. The models have relatively small horizontal grid spacing. 3. They performed well compared to other GCMs in representing basic aspects of observed climate at a regional scale [67]. The A1B and A2 scenarios were selected to typify the range of possible climate suitability for L. camara in 2030 and 2070. No scenarios from the B family of SRES scenarios were included in this paper because recent analyses of trends in factors such as global temperature and sea rise [68] showed that the observed increases were much higher than the hottest SRES scenario. The A1B scenario describes a balance between the use of fossil and non-fossil resources while A2 describes a varied world with high population growth but slow economic development and techno- logical change. The projection dates of 2030 and 2070 were chosen because they provide a reasonable snapshot of two periods, one in the near future in 20 years’ time and one much later in the future in 60 years’ time. Sutherst [40] and Kriticos and Leriche [69] suggested that using both native and exotic distribution data in fitting CLIMEX parameters could produce a model that better approximates the potential distribution of the taxa being modelled than one that relies solely on native range data. They suggested that 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 Hutchinsonian realized niche [70]. Stress parameters were fitted to the known native (Central and South America) and naturalized (South Africa and Asia) distribution of the species while the phenology data from Brazil was used to fit growth parameters [62–63]. Each of the parameters was adjusted iteratively until a satisfactory agreement was reached between the potential and known distribution of lantana in these areas. The fitted parameters were checked to ensure that they were biologically reasonable. Australian distribution data was reserved for validation of the model. Two cold stress mechanisms were used to define the southern limits of lantana distribution in Argentina and northern limits in Nepal, Pakistan and China. Lantana seldom occurs where temperatures frequently fall below 5 u C [71], and prolonged freezing temperatures kill aerial woody branches and cause defoliation [1]. Therefore, intolerance to frost was incorporated by accumulating stress when the average monthly minimum temperature fell below 5 u C with the frost stress accumulation rate (THCS) set at 2 0.004 week 2 1 . This cold-stress mechanism allowed the species to survive in Kathmandu (27 u 42 9 N 85 u 18 9 E) [72]. The Cold-Stress Degree-day Threshold (DTCS) was set at 15 u C days, with the stress accumulation rate (DHCS) set at 2 0.0022 week 2 1 so that the potential distribution was restricted to the known southern limits in Buenos Aires and northern limits in India, Nepal and China. This form of cold stress accounts for the need for the plant to grow at a minimal rate in order to offset respiration losses. If the temperatures are insufficient for the plant to grow this minimal amount, it needs to draw on photosynthate reserves. The heat stress parameter (TTHS) was set at 33 C, the same level as the limiting high temperature (DV3) with a stress accumulation rate (THHS) of 0.001 week 2 1 , which allowed lantana to persist ...

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... reasonable. Australian distribution data was reserved for validation of the model. Two cold stress mechanisms were used to define the southern limits of lantana distribution in Argentina and northern limits in Nepal, Pakistan and China. Lantana seldom occurs where temperatures frequently fall below 5 u C [71], and prolonged freezing temperatures kill aerial woody branches and cause defoliation [1]. Therefore, intolerance to frost was incorporated by accumulating stress when the average monthly minimum temperature fell below 5 u C with the frost stress accumulation rate (THCS) set at 2 0.004 week 2 1 . This cold-stress mechanism allowed the species to survive in Kathmandu (27 u 42 9 N 85 u 18 9 E) [72]. The Cold-Stress Degree-day Threshold (DTCS) was set at 15 u C days, with the stress accumulation rate (DHCS) set at 2 0.0022 week 2 1 so that the potential distribution was restricted to the known southern limits in Buenos Aires and northern limits in India, Nepal and China. This form of cold stress accounts for the need for the plant to grow at a minimal rate in order to offset respiration losses. If the temperatures are insufficient for the plant to grow this minimal amount, it needs to draw on photosynthate reserves. The heat stress parameter (TTHS) was set at 33 C, the same level as the limiting high temperature (DV3) with a stress accumulation rate (THHS) of 0.001 week 2 1 , which allowed lantana to persist along the Western Ghats [73] as well as in Bengal and Assam in India where it is reportedly common [57]. The dry stress parameter was set at the same level (0.1) as the lower soil moisture threshold (SM0) because soil moisture related stresses probably begin at the same soil moisture levels where growth stops. The stress accumulation rate of 2 0.01 week 2 1 was set to exclude the species from the drier western parts of South Africa where it survives only as an ornamental plant [74]. The wet stress threshold (SMWS) was set to 1.6 and the accumulation rate (HWS) set at 0.01 week 2 1 since lantana can tolerate up to 3000 mm of rainfall per year as long as the soil is not waterlogged for prolonged periods [1,75]. These settings allowed the species to grow well in Indonesia and the Philippines [53] as well as in central Burma, but excluded it from the wetter coastal areas [57]. In South Africa, lantana is found in areas with a mean annual surface temperature greater than 12.5 u C [76]. The seasonal phenology data for Iguazu (25 u 33 9 S, 54 u 34 9 W) in Brazil showed that ‘cold winter temperatures caused cessation of growth with a substantial loss in leaves and side-branches’ [63]. Winter temperatures in Iguazu can get as low as 8 u C. Thus, the limiting low temperature (DV0) was set at 10 u C to reduce growth appropriately during winter months in Iguazu. This value was chosen as a compromise between the South African distribution data and the phenology data from Iguazu. According to Day et al. [1], lantana does not appear to have an upper temperature limit. The summer temperatures in Iguazu rarely exceed 33 u C and thus the limiting high temperature DV3 was set at 33 u C, which allowed it to survive in Iguazu where it grows rapidly during summer [63]. The lower (DV1) and upper (DV2) optimal temperatures were set at 25 u C and 30 u C, respectively, based on seasonal phenology at Iguazu, and these provided a good fit to the observed distribution in South America, Asia and South Africa. The lower moisture threshold (SM0) was set at 0.1, correspond- ing to the permanent wilting point for many plants [35]. This excluded lantana from the drier western parts of South Africa where it survives only as an ornamental [74] but allowed it to survive in Israel where Danin [77] reported lantana as ‘a common component of the wasteland vegetation in the lowlands of the Mediterranean territories of Israel’. However, lantana may survive in certain areas of Israel due to irrigation since one of its other common habitats is irrigated cultivation such as date palm plantations and orchards [77]. The lower (SM1) and upper (SM2) optimum moisture thresholds were set at 0.5 and 1.2, respectively, to improve species growth during the months of January to March in Iguazu [63]. The upper soil moisture threshold (SM3) was set at 1.6 to allow it to grow in the Philippines and Indonesia where it has been reported as a troublesome weed [53]. The PDD thermal accumulation (number of degree days) mechanism did not appear to contribute to the definition of the South American or Asian distribution and so this parameter was not used. The parameters are shown in Table 1. These parameters were used to model potential lantana distribution under the reference climate (averaging period 1950–2000) as well as climate change scenarios described above. The modelled global climate suitability for lantana (Figure 2) compares well with its known native distribution in South and Central America as well as its exotic range in South Africa and Asia (Figure 1). A comparison of Figures 1 and 2 showed that the present global distribution of lantana is consistent with the Ecoclimatic Index values resulting from the CLIMEX model. Much of the tropics and subtropics are projected to have suitable climatic conditions for lantana. Large areas of South and Central America, the southern states of the USA, Asia, sub-Saharan Africa, Madagascar and the high volcanic Pacific island groups such as Fiji, Vanuatu, Samoa and New Caledonia, among others, have highly suitable climate for the species. Warm temperate areas such as northern New Zealand and southern Mediterranean Europe including Portugal, Italy and Greece are predicted to have unsuitable climates. The current and potential distribution of lantana in Australia is shown in Figure 3. The occurrence records for Australia, which were reserved for model validation and not used for model fitting, accord well with the modelled climate suitability for the continent, and the present Australian distribution is consistent with the Ecoclimatic Index. Approximately 87% of the occurrence records fall within the suitable and highly suitable categories. In Australia, the model projects much of the eastern coast from Cape York in northern Queensland to southern New South Wales (NSW) to be climatically suitable (Figure 3). However, no occurrence records were found for Cape York Peninsula because despite a few isolated infestations in this region, lack of human disturbance limits the rate of spread [78]. Coastal areas in south-west Western Australia are projected to have suitable climate for lantana, conforming to the actual distribution since small infestations occur in these areas [1]. Central Australia is projected as being unsuitable, mainly due to dry stress. For both the climate change models, a contraction in the suitable climate areas was observed worldwide (Figures 4, 5, 6, 7, 8, 9, 10, and 11) with this trend exacerbated in the 2070 scenario. The two GCMs showed moderately variable results but within each of the models, minimal sensitivity was seen between the two emission scenarios. In South America, suitable climate areas for lantana are substantially reduced throughout northern Argentina, Uruguay, Bolivia, Peru, Paraguay, large parts of Brazil, French Guiana, Surinam, Guyana, coastal Venezuela and Colombia. A similar trend is seen in Central America with suitable climate areas for lantana contracting in Panama, Costa Rica, Nicaragua, Honduras and Guatemala. By 2030, a reduction in suitable climate for lantana is projected in all of these countries and this trend is exacerbated by 2070 (Figures 6, 7, 10, and 11). Warming under future climate scenarios is projected to lead to a substantial reduction in suitable climate for lantana in this region. In North America, some differences can be seen between the two GCMs in coastal areas of southern states such as Florida, Louisiana and Texas in North America. Under the CSIRO-Mk3.0 GCM, these areas are projected to remain climatically suitable until 2070 (Figures 6 and 7) while the same areas are projected as marginal to unsuitable with the MIROC-H GCM (Figures 10 and 11). In Africa, suitable climatic areas for lantana are projected to contract substantially with only parts of Ethiopia, Uganda, Tanzania, Zambia, Angola, Gabon and Republic of Congo remaining suitable in 2070 under both GCMs and both SRES scenarios (Figures 6, 7, 10, and 11). Nevertheless, much of the continent shows high climatic suitability for lantana until 2030 (Figures 4, 5, 8, and 9). In South Africa, lantana range appears to expand further inland, mainly in the Eastern Cape and Kwazulu- Natal provinces, west of the Swaziland border as well as into Lesotho and this is particularly apparent by 2070 under both GCMs. In Asia, there is a considerable reduction in the projected potential range under climate change scenarios, especially for countries such as India, Sri Lanka, Myanmar, Thailand, Cambodia and Vietnam. However, in China the potential range shifts further inland and this is especially noticeable in the MIROC-H 2070 scenario (Figures 10 and 11). Lantana potential range shifts south into new areas in Australia (Victoria, South Australia and Tasmania) and a range expansion is seen in the south-west corner of Western Australia under both GCMs. Coastal areas in North Africa (Morocco and Algeria) and Southern Europe (Portugal, Spain, Italy and Greece) are projected to have suitable climate areas for lantana by 2070, particularly under the CSIRO-Mk3.0 GCM (Figures 6 and 7). This study has modelled the suitable climate area for Lantana camara under current climate and future climate scenarios using CLIMEX. The model provides a good fit to the current global distribution records as well as the current Australian distribution, which was reserved for model validation purposes. Under historical climate, much of the tropics and subtropics are modelled as having suitable climatic conditions for lantana. On ...