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Current and Potential Distribution of Senecio Madagascariensis Poir

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Current and Potential Distribution of Senecio Madagascariensis Poir Japanese Society of Grassland Science Japanese Society of Grassland Science ISSN1744-6961 ORIGINAL ARTICLE Current and potential distribution of Senecio madagascariensis Poir. (fireweed), an invasive alien plant in Japan Michio Tsutsumi National Agricultural Research Center for Western Region, Ohda, Shimane, Japan Keywords Abstract Invasive alien plant; macroclimatic environment; Maxent; potential distribution; The short-lived perennial (sometimes annual) plant, Senecio madagascariensis Senecio madagascariensis. Poir. (fireweed) is native to South Africa and Madagascar. This plant is an invasive weed becoming naturalized over a wide range of the world, and has caused agri- Correspondence cultural damage mainly due to its toxicity to livestock. In Japan, fireweed was first Michio Tsutsumi, National Agricultural found in 1976, and has been spreading throughout the country. In this study, the Research Center for Western Region, Ohda, Shimane 694-0013, Japan. current distribution of fireweed in Japan was investigated. Using a maximum Email: [email protected] entropy ecological niche modeling algorithm, the relationship between the distri- bution records of fireweed and climatic variables was modeled, and the potential Received 10 February 2011; distribution of fireweed was predicted. Many growing sites of fireweed have been Accepted 19 April 2011. observed on the Pacific coast and Seto Inland Sea coast. The northern and south- ern ends of the current distribution were the Pacific coast of southern Tohoku doi: 10.1111/j.1744-697X.2011.00222.x (36.9172°N, 140.8613°E) and southern Kyushu (31.5654°N, 130.3438°E), respec- tively. The results of modeling showed that mean temperature in the warmest quarter was the most influential predictor, and suggested that geographical distri- bution of fireweed in Japan is restricted mainly by temperature, not by precipita- tion. The predicted areas of potential distribution were mainly on the Pacific coast and eastern Seto Inland Sea coast. Of the regions where fireweed had not been found, the following regions were predicted as potential distribution areas of fire- weed: southern Kanto region along Tokyo Bay, coastal area of western Tokai region, western part of Seto Inland Sea coast and northern Kyushu. The Pacific coast of central Tohoku (39.058°N, 141.843°E) was predicted as the northern end of the potential distribution, and Amami-oshima Island (28.304°N, 129.519°E) as the southern end. Introduction 2008), Uruguay (Villalba and Ferna´ndez 2007), Brazil (Mat- zenbacher and Schneider 2008; Cruz et al. 2010) and Japan Fireweed (also called Madagascar fireweed, Madagascar rag- (Kinoshita et al. 1999). wort or Madagascar groundsel; Senecio madagascariensis In temperate and subtropical pastures along the south Poir., Asteraceae) is a short-lived perennial (sometimes, east coast of Australia, fireweed is commonly found (Sindel annual) plant native to South Africa and Madagascar (Hil- et al. 2008). Like many other Senecio species, fireweed pro- liard 1977). This plant is an invasive weed becoming natu- duces pyrrolizidine alkaloids (Gardner et al. 2006) which ralized over a wide range of the world such as Kenya (Sindel are poisonous to livestock; that is, it causes hepatopathy, and Michael 1992), coastal south-eastern Australia (Sindel reduces growth and in severe cases causes mortality when et al. 2008), Hawaii (Motooka et al. 2004; Le Roux et al. ingested. Cruz et al. (2010) reported that seven dairy cattle 2006), South Carolina (Sindel and Michael 1992; Kinoshita were affected and died due to fireweed poisoning in south- et al. 1999), Argentina (Verona et al. 1982; Lopez et al. ern Brazil. Although sheep and goats are less susceptible to ª 2011 The Author 150 Grassland Science ª 2011 Japanese Society of Grassland Science, Grassland Science, 57, 150–157 M. Tsutsumi Potential distribution of fireweed pyrrolizidine alkaloids poisoning than cattle and horses of greenhouse experiments, the results of additional experi- (Cheek 1998), fireweed was implicated in the death of 10 ments suggested that frost may not be as important a factor sheep in Australia (Seaman 1987). Since Iwasaki (2007) sug- in limiting the spread of fireweed (reviewed by Sindel et al. gested that fireweed has an allelopathic effect on other 2008). On the other hand, Sindel and Michael (1992) sug- plants, it is also supposed that invading fireweed depresses gested that high temperature may limit plant survival. Addi- the yield of some crops. tionally, fireweed can adapt to a semiarid environment In Japan, fireweed was first found on coastal reclaimed (Marohasy 1989). Sindel and Michael (1992) predicted the land in Naruto City, Tokushima Prefecture, in the eastern potential distribution of fireweed in Australia based on the Shikoku region (see Figure 1) in 1976 (Kinoshita et al. macroclimatic environment. They pointed out that the 1999). Since then, fireweed has spread over western Japan range of annual precipitation in the habitat of fireweed in (Kinoshita et al. 1999; Nakanishi 2001; Kochi Prefecture, Africa and South America, which is the most significant bio- Makino Memorial Foundation of Kochi Prefecture 2009). climatic factor on a continental scale in these regions, was Moreover, fireweed reached the Tohoku region of north- similar to that in Australia. Recently, Sindel et al. (2008) eastern Japan in 2006 (Fukushima Prefecture 2007). Fire- confirmed that the current distribution of fireweed had not weed was designated as an IAS (Invasive Alien Species) yet reached its potential distribution as predicted in 1992. under the Invasive Alien Species Act (which prohibits bring- In recent years, ecological niche modeling has been used ing, moving and growing a designated species) in 2006 by for a tool to assess potential geographic distributions of vari- the Japanese Government. It is important to predict the ous organisms: coral (Tittensor et al. 2009), insects (Ward potential distribution of fireweed to work out a control plan 2007; Roura-Pascual et al. 2009), amphibians (Kozak and for this species. Wiens 2006; Pawar et al. 2007; Rissler and Apodaca 2007), Though Sindel and Michael (1989) believed that low tem- reptiles (Pawar et al. 2007; Pearson et al. 2007), birds (Her- perature, specifically frost, is an important factor in limiting nandez et al. 2008), mammals (Hernandez et al. 2008) and the distribution of fireweed in Australia based on the results plants (Guisan et al. 2007; Fitzpatrick et al. 2008; Loarie Figure 1 Map of the study area with the recorded growing sites of fireweed (Senecio madagascariensis; n = 251) indicated as closed red circles. ª 2011 The Author Grassland Science ª 2011 Japanese Society of Grassland Science, Grassland Science, 57, 150–157 151 Potential distribution of fireweed M. Tsutsumi et al. 2008). It has also been applied to predicting the inva- Table 1 Climate profiles for fireweed (Senecio madagascariensis) sive potential of alien species (Ficetola et al. 2007; Ward based on 251 growing sites in Japan (my data) and 137 sites in Aus- 2007; Giovanelli et al. 2008; Roura-Pascual et al. 2009), tralia (reported by Sindel and Michael 1992) providing information for control of an invasion. Maximum value Minimum value In this study, the current distribution of fireweed in Japan was firstly investigated. Secondly, using a maximum entropy Climate variable† Japan Australia Japan Australia ecological niche modeling algorithm, the relationship between the distribution records of fireweed and climatic Annual mean temperature 17.5 20.1 12.6 11.1 variables was modeled to identify the climatic parameters Mean minimum coolest 3.8 8.6 )2.2 )1.3 determining the distribution. Finally, the potential distribu- month Mean maximum warmest 33.2 33.1 27.4 22.6 tion of fireweed was predicted using the model. month Annual temperature range 23.9 27.3 18.7 17.8 Materials and methods Mean temperature coolest 8.9 15.3 2.7 5.3 quarter Mean temperature warmest 26.4 25.4 21.8 16.5 Investigation of current distribution of fireweed quarter Information about the sites where fireweed was growing in Mean temperature wettest 26.2 25.4 19.6 7.1 quarter Japan was taken from the literature (Kinoshita et al. 1999; Mean temperature driest 11.0 22.8 2.7 6.9 Nakanishi 2001; Sugino 2008; Kochi Prefecture, Makino quarter Memorial Foundation of Kochi Prefecture 2009), a mailing Annual mean precipitation 2803 2397 1065 536 list (including information from non-experts), public Precipitation wettest month 469 418 166 54 websites, newspapers and personal communication (only Precipitation driest month 91 82 26 31 experts). Private websites such as blogs were also referred to. CV monthly precipitation 67.2 60.1 36.4 9.3 Based on the information obtained, a field survey was car- Precipitation wettest quarter 1062 1155 380 151 Precipitation driest quarter 303 272 100 108 ried out from July 2009 to August 2010. The fireweed grow- Precipitation coolest quarter 316 371 100 114 ing sites were attended, and the geographic information Precipitation warmest quarter 1062 1030 358 116 recorded at each site using a GPS receiver, eTrex VistaÒ C (Garmin International, Inc., Olathe, KS, USA). For the fol- †All temperatures are in °C and precipitations in mm. lowing analysis, the data obtained mainly by the field survey and partly from the literature and personal communication were used. The Tokyo Datum was used as the geographical Japan is an island country, and has a widely ranging topo- coordinate system in this paper. graphy. In the Mesh Climatic Data 2000 (Japan Meteoro- logical Agency 2002), a climatic database, the climate parameters in each of the third mesh (about 1 km2) only Macroclimatic data for making prediction of for Japan were estimated based on the climate data (values potential distribution of an average year, taken over 30 years from 1971 to 2000) Sindel and Michael (1992) successfully predicted the poten- from about 1000 meteorological stations. Thus, the Mesh tial distribution of fireweed in coastal south-eastern Austra- Climatic Data 2000 has a finer geographical scale than lia, mainly New South Wales, based on a range of 16 BIOCLIM or CLIMEX, and may have higher accuracy for parameters (as shown in Table 1) indicating the macro- Japan.
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