Japanese Society of Science

Japanese Society of Grassland Science ISSN1744-6961

ORIGINAL ARTICLE Current and potential distribution of madagascariensis Poir. (fireweed), an invasive alien 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 and . 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 (36.9172N, 140.8613E) and southern Kyushu (31.5654N, 130.3438E), 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 (39.058N, 141.843E) was predicted as the northern end of the potential distribution, and Amami-oshima Island (28.304N, 129.519E) 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., ) is a short-lived perennial (sometimes, east coast of , fireweed is commonly found (Sindel annual) plant native to South Africa and Madagascar (Hil- et al. 2008). Like many other Senecio , 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 (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), (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- , 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 Vista 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. Though the WorldClim database (Hijmans et al. climatic environment at the fireweed growing sites. They 2005), a climatic database, has the same spatial solution as used BIOCLIM (Busby 1986), a bioclimatic prediction system the Mesh Climatic Data 2000, it is based on the older data to make their prediction. In that system, various parame- (from 1960 to 1990). Therefore, the 16 climates variables ters of the climate were estimated for each 0.5 degree grid estimated by the Mesh Climatic Data 2000 were used for around the world. In recent years, many researchers used the following analysis. CLIMEX (Sutherst et al. 1999), a climate and population modeling solution, to predict the potential distribution of Prediction of potential distribution with invasive species (Potter et al. 2009; Watt et al. 2009; Chej- ecological niche modeling ara et al. 2010). In the CLIMEX system, the climate esti- mates for each 0.5 degree grid are derived from about 2400 Recently, Phillips et al. (2006) introduced the use of the meteorological stations worldwide (Sutherst et al. 1999). maximum entropy method (Maxent) for modeling species On the other hand, Japanese climate conditions may be geographic distributions with presence-only data (see considerably different within each 0.5 degree grid, since also Phillips 2008; Phillips and Dudı´k 2008). Maxent is a

ª 2011 The Author 152 Grassland Science ª 2011 Japanese Society of Grassland Science, Grassland Science, 57, 150–157 M. Tsutsumi Potential distribution of fireweed general-purpose machine learning method with a simple points (included 69 municipalities; Figure 1). Many fire- and precise mathematical formulation, and it has a number weed sites were observed on the Pacific coast and eastern of aspects that make it well-suited for species distribution Seto Inland Sea coast, especially in the areas around Awaji modeling. To approximate an unknown probability distri- Island and Osaka Bay. The northern end of the current dis- bution, the Maxent algorithm seeks the distribution with tribution in Japan was the Pacific coast of the southern maximum entropy subject to the constraint that the Tohoku region (36.9172N, 140.8613E, Iwaki City, Fuku- expected feature values under the estimated distribution shima Prefecture), and the southern end was the southern equal the empirically obtained values, on the basis of maxi- Kyushu region (31.5654N, 130.3438E, Hioki City, Kago- mum entropy principle. For modeling species distributions, shima Prefecture). Most of growing sites were extremely dis- the unknown probability becomes the species distribution turbed (artificially or naturally) areas such as roadsides, probability, and the features in the pixels of the target area road slopes, developed lands, flood plains and sea shores. comprise the environmental variables. Fireweed sites were also found on fallow fields and orchards. The relationship between the distribution records of fire- Table 1 lists the climate profiles for fireweed based on 251 weed and climatic variables was modeled using Maxent ver- sites in Japan and 137 sites in Australia (as reported by sion 3.3.3a (which is available at the following website: Sindel and Michael 1992) for comparison. Compared with http://www.cs.princeton.edu/~schapire/maxent/). The soft- the data from Japan and Australia, the maximum and ⁄ or ware default settings were adopted for model building. minimum values of several parameters were considerably Among the three types of probability value formats available different. It seemed that Japanese sites had hotter summers in the Maxent software, the cumulative value format was and colder winters than the Australian sites. It is evident selected for the prediction. The cumulative value for a pixel based on the molecular analysis that the origins of invasive (mesh) is computed as the sum of the probability of that fireweed population in Australia (also Hawaii) are KwaZul- pixel and all other pixels with equal or lower values, multi- u-Natal, South Africa (Scott et al. 1998; Radford et al. 2000; plied by 100 to produce a percentage. For model evaluation, Gardner et al. 2006; Le Roux et al. 2006). On the other receiver operating characteristic (ROC) analysis was used. hand, Kinoshita et al. (1999) presumed that fireweed popu- The area under the ROC curve (AUC), which can be an lation in Japan came from Kentucky with seeds for revegeta- indicator of the accuracy of model prediction, was calcu- tion; however, the origins were unknown. To specify the lated. The AUC ranges from 0.5 (random accuracy) to a origins of fireweed in Japan is required for discussing the maximum value of 1.0 (perfect discrimination). The differences between the climate variables in fireweed grow- 380 196 meshes were divided into 31 sets because the pro- ing sites in Japan and Australia. gram could not run without dividing the data into smaller sets. The program for each of the datasets was run, ran- Established ecological niche modeling and domly retaining 70% of the data for model training and the contribution of climatic variables remaining 30% for testing, to assess the average perfor- mance of the resulting models. The contribution of each cli- The AUC values from the predictive models of 176 training mate variable to the established model was evaluated with and 75 testing occurrence data for fireweed were consider- jackknife tests. In the jackknife test, each variable is excluded ably high, with mean AUCs of 0.982 and 0.973, respectively, in turn from the modeling framework, and a model is cre- for the training and the test data suggesting the high predic- ated with the remaining variables (i.e. drop contribution). tive power of the model. Alone contributions were also calculated by creating new Mean temperature in the warmest quarter was the most models with only one variable. To make prediction maps, a influential predictor among the 16 climatic parameters, cumulative threshold value that balances training omission, followed by mean minimum temperature in the coolest predicted area and threshold value (i.e. balancing commis- month, mean temperature in the coolest quarter and sion and omission errors) was used (Phillips et al. 2006). In annual mean temperature, when the variable contributions making prediction maps, all of the distribution records were were evaluated in isolation with a jackknife test (Figure 2). used. All the alone contributions of the eight variables derived from precipitation data were lower than those of the eight Results and discussion variables derived from temperature data. Thus, it was sug- gested that the geographical distribution of fireweed in Japan is restricted mainly by temperature, not by precipi- Current distribution of fireweed and climate tation. variables on the growing sites Response curves of fireweed to the gradients of the two Fireweed sites were found in 17 of the 47 prefectures of most influential predictors, mean temperature in the Japan, and geographic information was collected on 251 warmest quarter and mean minimum temperature in the

ª 2011 The Author Grassland Science ª 2011 Japanese Society of Grassland Science, Grassland Science, 57, 150–157 153 Potential distribution of fireweed M. Tsutsumi

(a)

(b)

Figure 2 The contribution of each climatic variable to the established model evaluated as regularized training gain, which measures good- ness-of-fit of training data to the model using jackknife tests. Open bars and closed bars indicate drop contributions and alone contribu- tions, respectively. coolest month, indicated that fireweed reacted to the two temperature components in unimodal and symmetric manners (Figure 3). The most suitable value of mean tem- perature in the warmest quarter for fireweed was 25.4C, and the range was between 23.5 and 27.7C, which exceeded the threshold value of 1.704. Similarly, the most suitable value of mean minimum temperature in the cool- est month was 1.9C, and the range was between )1.7 and 4.8C, which exceeded the threshold. These results Figure 3 Response curves of fireweed (Senecio madagascariensis)to also suggest that fireweed adapts to the hotter summers gradients of (a) mean temperature in the warmest quarter and (b) mean minimum temperature in the coolest month. and colder winters found in Japan than in Australia (see Table 1). Geographical distribution of a given plant species may be determined by not only climate condition, but geologi- areas of potential distribution were mainly on the Pacific cal features, soil properties and so on. In Japan, the data coast and Seto Inland Sea coast. Most of neighboring of topography, geological features, soil properties and land regions of the growing sites were predicted to be ‘suitable’, use for the third meshes are also available. On the other especially the coastal region centered on Awaji Island. Of the hand, as mentioned above, most of growing sites were regions where fireweed had not been found, the following extremely disturbed areas. Therefore, it was considered regions were predicted as potential distributed areas of fire- that the use of these variables for prediction would not be weed: the southern Kanto region along Tokyo Bay, the appropriate, and the prediction using only climate vari- coastal area of the western Tokai region, the western part of ables was made. Seto Inland Sea coast and the northern Kyushu region. All the meshes of Hokkaido, most meshes in the northern Tohoku region and the Sea of Japan coast were not pre- Potential distribution of fireweed dicted as suitable for fireweed. The northern end of the Development of the prediction map processed the distribu- mesh exceeding the threshold value was the Sea of Japan tion probabilities derived from the macroclimate-based eco- coast in the northern Tohoku region (39.871N, 139.844E, logical niche modeling with a threshold value of 1.704, to Oga City, Akita Prefecture). However, this was not predicted classify below-threshold values as predicted absence and to be the northern end of potential distribution because transform them into null values (Figure 4). The predicted there was only one mesh exceeding the threshold value in

ª 2011 The Author 154 Grassland Science ª 2011 Japanese Society of Grassland Science, Grassland Science, 57, 150–157 M. Tsutsumi Potential distribution of fireweed

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Figure 4 Predicted potential geographic distribution for fireweed (Senecio madagascariensis) in Japan resulting from Maxent climatic modeling using presence records (see legend in the figure). White areas indicate water. See also Figure 1 for the place names. this area. Therefore it was predicted that the pacific coast of Acknowledgments central Tohoku (39.058N, 141.843E, Ofunato City, Iwate Prefecture) was the northern end of potential distribution. This study was funded by the Ministry of Agriculture, For- Though each mesh on Iriomote Island (24.287N, estry and Fisheries of Japan (MAFF) and carried out under 123.894E, Taketomi Town, Okinawa Prefecture) and the the guidance of the Animal Products Safety Division, Food northern part of Okinawa Island (26.729N, 128.294E, Safety and Consumer Affairs Bureau of MAFF. I am grateful Kunigami Village, Okinawa Prefecture) exceeded the to Reiko Baba, Setsuko Desaki, Masahito Inoue, Koji Kana- threshold value, similarly, they were not predicted to be the oka, Shunji Kurokawa, Kazuo Murai, Kentaro Murakami, southern end of potential distribution. It was predicted that Makoto Ogawa, Tadahisa Ohmachi, Akira Sakamoto, Yoshi- Amami-oshima Island (28.304N, 129.519E, Tatsugo ro Sato, Takao Sugino and Shuji Uyemura for providing Town, Kagoshima Prefecture) was the southern end of the information about fireweed growing sites. I would like to potential distribution. thank Katsuhiro Aikawa and Shigeru Miyazaki for support- Fireweed may reproduce mainly by seeds while vegetative ing this research. The assistance of Chisato Tsutsumi in the reproduction of this species has also been observed field is gratefully acknowledged. (reviewed by Sindel 2009). Many growing sites in artificially disturbed areas were observed in this field survey. Therefore, References it is predicted that human activity unintentionally disperses the seeds of fireweed, for example, by moving soil and sand Busby JR (1986) Bioclimate Prediction System (BIOCLIM). for civil engineering works. Though great agricultural dam- User’s Manual Version 2.0. Australian Biological Resources age by fireweed has not been reported in Japan at present, Study Leaflet, Canberra, Australia. the invasion of fireweed should be under surveillance in the Cheek PR (1998) Pirrolyzidine alkaloids. In: Natural Toxicants potential distributed areas; especially in the neighboring in Feeds, Forages, and Poisonous Plants (Ed Cheek PR), regions to growing sites. Interstate Publishers, Danville, USA, 338–363.

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