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Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Erwinia amylovora in China
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Agricultural Sciences in China 2007, 6 ( 6 ) :688-605
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*,""
ScienceDirect
June 2007
Potential Distribution of Alien lnvasive Species and Risk Assessment: a Case Study of EwMa amylovora in China CHEN Chen*,CHEN Juan*,HU Bai-shi, JIANG Ying-hua and LIU Feng-quan Kev Laboratory of Monitoring and Management Nanjing 21009.5, P.R.China
if
Plant Diseases and Insects, Ministry of Agriculture, Nanjing Agricultural University,
Abstract Alien invasive species represent a severe risk to biodiversity and economy, as in the case of fKe blight (Erwinia amylovora), a bacterial disease that originated in North America, which may be released into new locations by means of fruit trade. On the basis of the knowledge of Erwinia amylovora's biophysical characteristics and environmental data, the geographic information system (GIS) has been applied to determine areas where Erwinia amylovora can potentially invade China. Temperature and precipitation, during the blossoming period, are considered to be two critical factors affecting the Erwinia amylovoru's suitable climatic zones. This spatial modeling approach was validated from a case study in Europe, where the occurrence of Erwinia amylovora has been proven. The model prediction agreed with the occurrence of the bacteria recorded in Europe, and the same procedure has been applied to produce a potential establishment area in China's two preferential apple cultivation regions, Bohai Bay region and Huangtu Altiplano region. It has been found that areas belonging to the high-risk category are more or less the main apple producing areas, accounting for their great economic importance in China. This methodology provides an initial baseline for assessment, prevention, and management of alien species that may become invasive under certain environmental conditions. In addition, this modeling approach provides a tool for policy makers to use, in making decisions on management practices where alien species are involved.
Key words: biological invasions, Erwinia amylovora, CIS, potential distribution, risk assessment
INTRODUCTION The introduction of an invasive species into the new environment can represent a severe risk to biodiversity (Hobbs 2000; van Auken 2000; Mooney and Cleland 2001), as well as to agriculture, forestry, and fisheries (Reichard and Hamilton 1997; Ricciard and Rasmussen 1999). Fire blight (Erwiniaamylovora) is a bacterium originating in North America. It has been spreading rapidly in recent decades, almost into the entire European continent (Fig.l), and its presence has frequently led to trade barriers against countries where it is estab-
lished (Roberts et al. 1998; van der Zwet 1996). The characteristic symptom of fire blight disease is that the affected plant parts appear to have been scorched by fire. Erwinia amylovora can infect blossoms, fruit, stems, leaves, and woody branches. A canker is formed when an infection progresses into larger branches and trunks. Infected tissues produce characteristic ooze, a sticky substance containing bacteria and plant sap. In spring, the bacteria are carried by wind-blown rain or insects (such as flies) from oozing cankers to blossoms or young tender tissues of shoots where infection may start (Yamamura et al. 2001). Then, pathogens on the blossoms are rapidly transmitted to other
This paper IS translated from its Chinese version in Scientia Agriculnrra Sinica. CHEK Chen. Tel: +86-344396726, E-mail: [email protected]; Correspondence LIU Feng-quan. Tel: +86-25-84396726, E-mail: fqliu20011 @sina.corn.cn 'These authors contributed equally to this paper.
Q W 7 .CAAS.All rights resewed. Publishedby Elmvier LM.
Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Envinia amylovora in China
blossoms by rain or pollinating insects such as honeybees (Agrios 1988; Thomson 2000). The bacteria enter blossoms through natural openings, such as nectaries. After killing the blossom, the blight infection moves into the flower stem and then into the peduncle and spur, where it invades the leaves and finally the branch. Fire blight disease can attack at least 174 species in 39 genera of the family Rosaceae, including fruit trees, such as apple, pear, plum, apricot, sweet cherry, and loquat. Other hosts include quince, mountain ash, cotoneaster, hawthorn, raspberry, and blackberry (van der Zwet and Keil 1979). The expansion of the global apple fruit trade has fostered an explosion of unintentional species introduction that has spread beyond their native range. In recent years, thousands of apple and pear scions have imported into Hebei, Shandong, and Liaoning provinces, China, from Holland, Japan, and the United States. There are great varieties of rosaceae plants cultivated in China, which are susceptible to Erwinia amylovora. Two preferential apple cultivation regions in China, the Bohai Bay region and the Huangtu Altiplano region, have been focused on in this article, with apple cultivars accounting for 44 and 34% of the nation's overall production, respectively. On the whole, they contribute to almost 90% of the nation's apple export. Thus, there is an urgent need to specify the potential establishment risk in these two regions and implement preventive risk management practices to guarantee the
689
conservation of apple cultivars in China.
MATERIALS AND METHODS Methodology The Erwinia amylovora may thrive under humid and warm climatic conditions, which have a crucial effect on its outbreak during the blossoming period. Research by Zhao and Lin (1995) identified ecological factors limiting the bacteria's distribution. These ecological factors, such as temperature and precipitation can be gathered, edited, and analyzed with the help of the geographic information system (GIs). Spatial and dynamic results are demonstrated, thus opening the doors for matching an organism's biological response parameters with the environmental bioclimatic variables, within a geographical area. A more comprehensive meteorological and host database was used to reanalyze the Erwinia amylovora's distribution in China's two preferential apple cultivation regions, as well as its relationship with the ecological factors.
Biophysical parameters Steiner (1990a, b) developed a predictive program for forecasting fire blight disease in apples based on variables including daily minimum and maximum
. Fig. 1 Worldwide distribution of the fire blight as demonstrated by GIs. Areas in black shade indicate countries where the occurrence of the fire blight has been proved.
02007, CA4S.All rights reserved. Publishedby ElsevlerLtd.
690
temperature, rainfall, and leaf wetness. It predicts the progress of the disease by calculating degree-hours and degree-days. The conditions of blossom blight are: Flowers are open; accumulation of at least 110 DH > 18.3"C within the last 44.4 DD > 14.4"C for apples; a rainfall of 0.25 mm or greater during the current day, or 2.5 mm during the previous day; and daily average temperature greater than or equal to 15.6"C. This model has been widely used in many countries around the world. Smith (1993) developed the cougar blight model, for which the environmental factors were: rainfall, leaf wetness, and temperature. It was predicted by calculating the degree hours above 15.6"C during 96 hours. Prediction of flower colonization suggested by Thomson et a1 (1982) was based on the daily mean temperature ring above a line drawn from 16.7"C on March J to 14.4"Con May 1 (Billing 1992, 1996). Tlus model did not take into account the presence of the pathogen. By referring to these models, the temperature and precipitation during the flowering of apples are considered as the ecological indexes for potential establishment analysis of Ewinia amylovora.
Meteorological and apple cultivars' distribution database European meteorological data of approximately 400 weather observation stations were included in this analysis. The data available was the average temperature of a period of ten days, in the format of the average number in the recent two decades, rather than year by year. The temperature and precipitation indices during the apple blossom period were extracted. The National Center of Atmospheric Research of the United States provided the European meteorological data. Chinese national meteorological data was comprised of 730 weather observation stations, for 25 years (1981-2005). The data used were the average temperature and precipitation (rainfallj every day. Chinese meteorological data was provided by the Meteorological Information Center, Chinese National Weather Bureau. This research focuses on the two preferential apple cultivation regions in China: Bohai Bay and Huangtu
CHEN Chen et al.
Altiplano regions, especially their subordinate preferentially supported counties for apple cultivation.
Model building: potential establishment area predicted by GIS A list of geographic terms, containing additional attributes from the meteorological and host database was exported into Excel spreadsheets. The Excel files were then converted to dbase IV (.dbf) for use in ArcGIS. An ArcGIS scripting language was used to convert the location from degrees/minutes/seconds to decimal degrees, as required by ArcGIS. Finally, the dbase 1V file was imported into the ArcGIS 9.0 and a shapefile from the converted latitude/longitudelocations was created using the "add X, Y" function ArcGIS 9.0. Various models were run repeatedly to compare the risk maps with the geographical distribution. Finally, the model parameters were examined for consistency by comparing them with the data of the European continent, if they were available. The geographical distribution of the Erwinia amylovora quarantine area in the European continent was used to estimate the parameter values. All the current simulations were run using the parameter values in Table. The simulations were conducted in the ArcMap Spatial Analyst extension, which allows us to interpolate the temperature and precipitation point data to raster grids. The inverse distance weighted interpolation method, which estimates cell values, by averaging values of sample points in the vicinity of each cell, were specifically chosen. The closer the point was to the center of the cell, the more influence, or weight, it had on the averaging process. The resulting raster had interpolated the grid into the land area or spatial space where there was no data. The result would be raster surfaces of temperature and precipitation values, respectively. The raster calculator, which was another part of the Spatial Analyst extension, could be used to perform a query, using Map Algebra, on one or more of the raster layers and output a single raster layer as the result. The raster calculator would be used to create a new grid, to display the conjunct area between the temperature and precipitation rasters. The conjunct grid was generated by multiplying the temperature and precipitation rasters.
02007, CAAS. All rightsreserved. Publishedby Elsvkr LM.
Potential Distribution of
69 1
Alien Invasive Species and Risk Assessment: a Case Study of Enviniu arnylovoru in China
The rasters were reclassified into four risk ranks according to the biological indices listed in Table, namely high-risk area, medium-risk area, low-risk area, and no-risk area. Finally, polygons of supported counties were overlaid on the risk map, to determine counties falling under each predicted potential risk rank.
RESULTS Validation of the selected biologicalindices A potential establishment risk map for the entire European continent based on the precipitation and temperature interpolated raster maps was initially modeled (Figs.
2,3, and 4). Because of the limitation of available European meteorological data, only one risk map of Europe was produced based on the average indices of the recent two decades. According to the results predicted by GIs, Erwinia amylovora can become potentially invasive in most parts of the central and southern European continent. Central Great Britain, Ireland, northern Portugal, northern Italy, Switzerland, southern Germany, Austria, Slovenia, Albania, western Bulgaria, and central Romania are high-risk rank regions. Great Britain, northern Spain, France, Belgium, Netherlands, western Germany, central Italy, western Czech Republic, Slovakia, Hungary, Croatia, Serbia and Montenegro,Macedonia, Romania, Bulgaria, southwestem Ukraine, and central part of Byelarus are located in
Table Risk rank of supported counties in two apple cultivation regions and assessing parameters Location Yan'an City Weinan City Xianyang City Baoji City Tongchuan City Yuncheng City Linfen City Sanmenxia City Luoyang City Qingyang City Weihai City Dalian City Pingliang City
Yantai City Zibo City Linyi City Zaozhuang City Rizhao City Qingdao City Huludao City Yingkou City Qinghuangdao City
Risk rank
Temperature during blossom period ("C)
Precipitation during blossom period (mm)
High risk
> 16.7
> 2.5
Medium risk
15.6- 16.7
2-2.5
Low risk
14.4-15.6
1.5-2
50"N
40"N Temperature durmg blossom penod ('c)
m
014.4-15.6 10"W
0"E
IO"E
20'E
30"E
= 15.6-16.7 16.7-3 1
Fig. 2 Interpolation of temperature index during the blossom period in the European continent.
02007, CAAS. All rlghts r e s a d . PuMishedby Elsevier Ltd.
692
CHEN Chen et ul.
the medium-risk rank. These results correspond with field observations of the Erwinia amylovora recorded in Europe.
The same procedure was followed in China to obtain a more accurate picture. All together, 25 risk maps were calculated on the year-by-year basis, and then their av-
Fig. 3 Interpolation of precipitation index during the blossom period in the European continent.
-70"
- 60" N
-50"N
-40" N
-
Potential nsk
I&E
30' E
No nsk Low nsk
Medium nsk High nsk 0 country
Fig. 4 Potential risk of Entvnia urnylovor In European continent
92007, CAAS. All rights reserved.Publishedby Elsewer Ltd.
Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Envinia amylovora in China
erage helped to get an average risk map of Erwinia amylovora. By superposing the risk map on a China map (specific to counties), counties with their corresponding risk ranks were displayed clearly. It was found that the distributionof the risk area of Eminia umylovoru
11'4-E
1lf"E
693
was similar to the distribution of the apple cultivation regions, which were of great importance to fruit production. In Bohai Bay apple cultivation region, the 28 preferentially supported counties are depicted in shadow in Fig.5. It is found that these counties are
12i)"E
l2j-E
Fig. 5 Potential 25-year-average risk in Bohai Bay apple cultivation region.
Supported counue\
105"E
108"E
Fig. 6 Potential 25-year-average risk in Huangtu altiplano apple cultivation region.
02007, CAAS. All flghts reserved. Published by ElsevierLM.
6Y 4
mostly located in the high- and moderate-riskrank areas. In the Huangtu Altiplano apple cultivation region (Fig. 6), there are 27 preferentially supported counties, which are similar to the ones depicted in the shadow in F i g 5 Similarly. it can be found that the preferentially supported counties are mostly in the high- and mediumrisk ranks, in which more than half of the preferentially supported counties are in the high-risk area rank. Only the Pingliang disrtict belongs to the low-risk rank, all the rest belongs to the medium-risk rank. The preferentially supported counties in these two regions and their corresponding risk ranks are listed in Table. The ecological environment in these two regions is fragile. There are serious losses on account of run-off soil, therefore, if the Eminia amylowm invades China, it will cause great ecological disasters as well as economic losses. Besides apple fruits, there are still a large number of host species cultivated everywhere throughout China. which are susceptible to Erwinia arnylovora, indicating a severe threat to biological diversifications.
DISCUSSION Erwinia amylovora has long been recognized as a severe invasive fruit disease in many countries throughout the world, with fruit growers frequently complaining of substantial economic losses. Through the risk analysis by GIS, it is found that a large part of China ha5 a suitable ecological environment for this disease. Considering the scale of cultivated apple areas in China, however, these results suggest significant economic impacts of Erwinia amylovora on these fruits. Thus, prevention and early detection will be the focus of most management efforts toward invasive pathogens. Once invaders establish, there is often no going back because of the difficulty of eradication. Tools are urgently needed to forecast the future invaders’ spread, and to assess the worthiness of prevention efforts (Clark et al. 2001; Leung ef al. 2002). Managers need a way to prioritize and direct prevention efforts to known invaders (van der Zanden et al. 2004). Advances are also being made to identify the troublesome invaders of the future; for example, several recent studies use a risk assessment framework to identify potential invaders (Kolar and Lodge 2002; Ricciardi and Rasmussen 1998). Risk assessment of an invasive species is generally con-
CHEN Chen et al.
ducted to inform two classes of risk management decisions: (1) those regarding the introduction of potentially invasive nonindigenous species, their vectors, or conveyances prior to establishment (leading to decisions to authorize, prohibit, or permit activities under specified conditions), and (2) decisions regarding the allocation of scarce resources for the control of established invasive species, including rapid response to emerging threats. Risk management is the process of identifying, evaluating, selecting, and implementing actions to reduce risk (Andersen et al. 2004). Although efforts have been made to describe the attributes of successful invaders and invasible ecological communities (Orians 1986), ecologists have lamented the difficulty in making quantitative predictions about invaders (Lodge 1993), and the broad-scale statistical patterns of the invaders’ success still remains pretty much in the dark. The geographical approach, outlines the potential distribution of alien species, as a first step to determine which may be potentially invasive, as well as provides guidelines to diminish future impacts in specific regions. This approach is inexpensive and based on reliable validation. This procedure can be generalized for almost any species. Likewise, this methodology can also be included in the risk analysis protocol to provide a valuable initial baseline for implementing integrated pest assessment, prevention, and management of alien species that could potentially become invasive under certain environmental conditions. To sum up, this methodology, as exemplified here, is a low-cost, robust tool, with applicability to many other pest taxa and agricultural regions worldwide.
Acknowledgements This study was supported by the National 973 Program of China (2002CB111405). We would like to thank the Archives of Center Meteorological Bureau, China, as well as the National Center of Atmospheric Research of the United States, for their generous provision of the meteorological data.
References Agrios G N. 1988. Plant Pathology. 3rd ed. Academic Press, New York. Andersen M C, Adams H, Hope B, Powell M. 2004. Risk assessment for invasive species. Risk Analysis, 24,787-793. Billing E. 1992. Billing’s revised system for fire blight risk
02007,CAAS.All rightsreserved. Publishedby Elsevier Ltd.
Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Enviniu umylovoru in China assessment. EPPO Bulletin, 22, 1-102. Billing E. 1996. BIS95, an improved approach to fire blight risk assessment.Acta Horticulturae, 411, 121-126. Clark J S, Carpenter S R, Barber M, Collins S, Dobson A, Foley J A, Lodge D M, Pascual M, Jr Pielke R, Pizer W, Pringle C, Reid W V, Rose K A, Sala 0, Schlesinger W H, Wall D H, Wear D. 2001. Ecological forecasts: an emerging imperative. Science, 293,657-660. Hobbs R J. 2000. Land-use changes and invasions. In: Mooney H A, Hobbs R 3, eds, Invasive Species in A Changing World. Island Press, Washington DC. pp. 55-64. Kolar C S, Lodge D M. 2002. Ecological predictions and risk assessment for alien fishes in North America. Science, 298, 1233-1236. Leung B, Lodge D M, Finnoff D, Shogren J F, Lewis M A, Lamberti G. 2002. An ounce of prevention or a pound of cure: bioeconomic risk analysis of invasive species. Proceedings: Biological Sciences, 269,2407-2413. Lodge D M. 1993. Biological invasions: lessons for ecology. Trends in Ecology and Evolution, 8, 133-137. Mooney H A, Cleland E E. 2001. The evolutionary impact of invasive species. Proceedings of the National Academy of Sciences of the USA, 98,5446-5451. Orians G H. 1986. Site characteristics favoring invasions. In: Mooney H A, Drake J A, eds, Ecology of Biological Invasions of North America and Hawaii. Springer,New York. pp. 133148. Reichard S H, Hamilton C W. 1997. Predicting invasions of woody plants introduced to North America. Conservation Biology, 11, 193-203. Ricciard A, Rasmussen J B. 1999. Extinction rates of North American freshwater fauna. Conservation Biology, 13,12201222. Ricciardi A, Rasmussen J B. 1998. Predicting the identity and impact of future biological invaders: a priority for aquatic resource management. Canadian Journal of Fisheries and Aquatic Sciences, 55, 1759-1765. Roberts R G, Hale C N, van der Zwet T, Miller C E, Redlin S C.
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1998. The potential for spread of Erwinia amylovora and fire blight via commercial apple fruit; a critical review and risk assessment. Crop Protection, 17, 19-28. Smith T J. 1993. A predictive model for forecasting fire blight of pear and apple in Washington state. Acta Horticulturae, 338, 153-160. Steiner P W. 1990a.Predicting apple blossom infection by Erwinia amylovora using the MARYBLYT model. Acta Horticulturae, 273, 139-148. Steiner P W. 1990b. Predicting canker, shoot and trauma blight phases of apple fire blight dpidemics using the Maryblyt model. Acta Horticulturae, 273, 149-158. Thomson S V, Schroth M N, Molker W J, Reil W 0. 1982. A forcasting model for fire blight of pear. Plant Diesase, 66, 576-579. Thomson S V. 2000. Epidemiology of fire blight. In: Vanneste J L, ed, Fire Blight: The Disease and Its Causative Agent, Erwinia amylovora. CABI, New York. pp. 9-36. van Auken 0 W. 2000. Shrub invasions of North America semiarid grasslands. Annual Review of Ecology and Systematics, 31, 197-215. van der Zanden M J, Olden J D, Thorne J H, Mandark N E. 2004. Predicting occurrences and impacts of smallmouthbass introductions in north temperate lakes. Ecological Applications, 14, 132-148. van der Zwet T, Keil H L. 1979. Fire blight: A bacterial disease of rosaceous plants. In: Agriculture Handbook. Vol. 510. United States Department of Agriculture, Washington DC. van der Zwet T. 1996. Present worldwide distribution of fire blight. Acta Horticulturae, 411,7-8. Yamamura K, Katsumata H, Watanabe T. 2001. Estimating invasion probabilities: a case study of fire blight disease and the importation of apple fruits. Biological Invasions, 3,373378. Zhao Y F, Lin W. 1995. Primary research on potential establishment area of the fire blight using geographic information system. Plant Quarantine, 6, 321-326. (in Chinese) (Edited by WANG Lu-han)
Qm7, CAAS. All righls menred. P u M i by Elsevier Ltd.
Agricultural Sciences in China 2007, 6 ( 6 ) :688-605
--rd + -
*,""
ScienceDirect
June 2007
Potential Distribution of Alien lnvasive Species and Risk Assessment: a Case Study of EwMa amylovora in China CHEN Chen*,CHEN Juan*,HU Bai-shi, JIANG Ying-hua and LIU Feng-quan Kev Laboratory of Monitoring and Management Nanjing 21009.5, P.R.China
if
Plant Diseases and Insects, Ministry of Agriculture, Nanjing Agricultural University,
Abstract Alien invasive species represent a severe risk to biodiversity and economy, as in the case of fKe blight (Erwinia amylovora), a bacterial disease that originated in North America, which may be released into new locations by means of fruit trade. On the basis of the knowledge of Erwinia amylovora's biophysical characteristics and environmental data, the geographic information system (GIS) has been applied to determine areas where Erwinia amylovora can potentially invade China. Temperature and precipitation, during the blossoming period, are considered to be two critical factors affecting the Erwinia amylovoru's suitable climatic zones. This spatial modeling approach was validated from a case study in Europe, where the occurrence of Erwinia amylovora has been proven. The model prediction agreed with the occurrence of the bacteria recorded in Europe, and the same procedure has been applied to produce a potential establishment area in China's two preferential apple cultivation regions, Bohai Bay region and Huangtu Altiplano region. It has been found that areas belonging to the high-risk category are more or less the main apple producing areas, accounting for their great economic importance in China. This methodology provides an initial baseline for assessment, prevention, and management of alien species that may become invasive under certain environmental conditions. In addition, this modeling approach provides a tool for policy makers to use, in making decisions on management practices where alien species are involved.
Key words: biological invasions, Erwinia amylovora, CIS, potential distribution, risk assessment
INTRODUCTION The introduction of an invasive species into the new environment can represent a severe risk to biodiversity (Hobbs 2000; van Auken 2000; Mooney and Cleland 2001), as well as to agriculture, forestry, and fisheries (Reichard and Hamilton 1997; Ricciard and Rasmussen 1999). Fire blight (Erwiniaamylovora) is a bacterium originating in North America. It has been spreading rapidly in recent decades, almost into the entire European continent (Fig.l), and its presence has frequently led to trade barriers against countries where it is estab-
lished (Roberts et al. 1998; van der Zwet 1996). The characteristic symptom of fire blight disease is that the affected plant parts appear to have been scorched by fire. Erwinia amylovora can infect blossoms, fruit, stems, leaves, and woody branches. A canker is formed when an infection progresses into larger branches and trunks. Infected tissues produce characteristic ooze, a sticky substance containing bacteria and plant sap. In spring, the bacteria are carried by wind-blown rain or insects (such as flies) from oozing cankers to blossoms or young tender tissues of shoots where infection may start (Yamamura et al. 2001). Then, pathogens on the blossoms are rapidly transmitted to other
This paper IS translated from its Chinese version in Scientia Agriculnrra Sinica. CHEK Chen. Tel: +86-344396726, E-mail: [email protected]; Correspondence LIU Feng-quan. Tel: +86-25-84396726, E-mail: fqliu20011 @sina.corn.cn 'These authors contributed equally to this paper.
Q W 7 .CAAS.All rights resewed. Publishedby Elmvier LM.
Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Envinia amylovora in China
blossoms by rain or pollinating insects such as honeybees (Agrios 1988; Thomson 2000). The bacteria enter blossoms through natural openings, such as nectaries. After killing the blossom, the blight infection moves into the flower stem and then into the peduncle and spur, where it invades the leaves and finally the branch. Fire blight disease can attack at least 174 species in 39 genera of the family Rosaceae, including fruit trees, such as apple, pear, plum, apricot, sweet cherry, and loquat. Other hosts include quince, mountain ash, cotoneaster, hawthorn, raspberry, and blackberry (van der Zwet and Keil 1979). The expansion of the global apple fruit trade has fostered an explosion of unintentional species introduction that has spread beyond their native range. In recent years, thousands of apple and pear scions have imported into Hebei, Shandong, and Liaoning provinces, China, from Holland, Japan, and the United States. There are great varieties of rosaceae plants cultivated in China, which are susceptible to Erwinia amylovora. Two preferential apple cultivation regions in China, the Bohai Bay region and the Huangtu Altiplano region, have been focused on in this article, with apple cultivars accounting for 44 and 34% of the nation's overall production, respectively. On the whole, they contribute to almost 90% of the nation's apple export. Thus, there is an urgent need to specify the potential establishment risk in these two regions and implement preventive risk management practices to guarantee the
689
conservation of apple cultivars in China.
MATERIALS AND METHODS Methodology The Erwinia amylovora may thrive under humid and warm climatic conditions, which have a crucial effect on its outbreak during the blossoming period. Research by Zhao and Lin (1995) identified ecological factors limiting the bacteria's distribution. These ecological factors, such as temperature and precipitation can be gathered, edited, and analyzed with the help of the geographic information system (GIs). Spatial and dynamic results are demonstrated, thus opening the doors for matching an organism's biological response parameters with the environmental bioclimatic variables, within a geographical area. A more comprehensive meteorological and host database was used to reanalyze the Erwinia amylovora's distribution in China's two preferential apple cultivation regions, as well as its relationship with the ecological factors.
Biophysical parameters Steiner (1990a, b) developed a predictive program for forecasting fire blight disease in apples based on variables including daily minimum and maximum
. Fig. 1 Worldwide distribution of the fire blight as demonstrated by GIs. Areas in black shade indicate countries where the occurrence of the fire blight has been proved.
02007, CA4S.All rights reserved. Publishedby ElsevlerLtd.
690
temperature, rainfall, and leaf wetness. It predicts the progress of the disease by calculating degree-hours and degree-days. The conditions of blossom blight are: Flowers are open; accumulation of at least 110 DH > 18.3"C within the last 44.4 DD > 14.4"C for apples; a rainfall of 0.25 mm or greater during the current day, or 2.5 mm during the previous day; and daily average temperature greater than or equal to 15.6"C. This model has been widely used in many countries around the world. Smith (1993) developed the cougar blight model, for which the environmental factors were: rainfall, leaf wetness, and temperature. It was predicted by calculating the degree hours above 15.6"C during 96 hours. Prediction of flower colonization suggested by Thomson et a1 (1982) was based on the daily mean temperature ring above a line drawn from 16.7"C on March J to 14.4"Con May 1 (Billing 1992, 1996). Tlus model did not take into account the presence of the pathogen. By referring to these models, the temperature and precipitation during the flowering of apples are considered as the ecological indexes for potential establishment analysis of Ewinia amylovora.
Meteorological and apple cultivars' distribution database European meteorological data of approximately 400 weather observation stations were included in this analysis. The data available was the average temperature of a period of ten days, in the format of the average number in the recent two decades, rather than year by year. The temperature and precipitation indices during the apple blossom period were extracted. The National Center of Atmospheric Research of the United States provided the European meteorological data. Chinese national meteorological data was comprised of 730 weather observation stations, for 25 years (1981-2005). The data used were the average temperature and precipitation (rainfallj every day. Chinese meteorological data was provided by the Meteorological Information Center, Chinese National Weather Bureau. This research focuses on the two preferential apple cultivation regions in China: Bohai Bay and Huangtu
CHEN Chen et al.
Altiplano regions, especially their subordinate preferentially supported counties for apple cultivation.
Model building: potential establishment area predicted by GIS A list of geographic terms, containing additional attributes from the meteorological and host database was exported into Excel spreadsheets. The Excel files were then converted to dbase IV (.dbf) for use in ArcGIS. An ArcGIS scripting language was used to convert the location from degrees/minutes/seconds to decimal degrees, as required by ArcGIS. Finally, the dbase 1V file was imported into the ArcGIS 9.0 and a shapefile from the converted latitude/longitudelocations was created using the "add X, Y" function ArcGIS 9.0. Various models were run repeatedly to compare the risk maps with the geographical distribution. Finally, the model parameters were examined for consistency by comparing them with the data of the European continent, if they were available. The geographical distribution of the Erwinia amylovora quarantine area in the European continent was used to estimate the parameter values. All the current simulations were run using the parameter values in Table. The simulations were conducted in the ArcMap Spatial Analyst extension, which allows us to interpolate the temperature and precipitation point data to raster grids. The inverse distance weighted interpolation method, which estimates cell values, by averaging values of sample points in the vicinity of each cell, were specifically chosen. The closer the point was to the center of the cell, the more influence, or weight, it had on the averaging process. The resulting raster had interpolated the grid into the land area or spatial space where there was no data. The result would be raster surfaces of temperature and precipitation values, respectively. The raster calculator, which was another part of the Spatial Analyst extension, could be used to perform a query, using Map Algebra, on one or more of the raster layers and output a single raster layer as the result. The raster calculator would be used to create a new grid, to display the conjunct area between the temperature and precipitation rasters. The conjunct grid was generated by multiplying the temperature and precipitation rasters.
02007, CAAS. All rightsreserved. Publishedby Elsvkr LM.
Potential Distribution of
69 1
Alien Invasive Species and Risk Assessment: a Case Study of Enviniu arnylovoru in China
The rasters were reclassified into four risk ranks according to the biological indices listed in Table, namely high-risk area, medium-risk area, low-risk area, and no-risk area. Finally, polygons of supported counties were overlaid on the risk map, to determine counties falling under each predicted potential risk rank.
RESULTS Validation of the selected biologicalindices A potential establishment risk map for the entire European continent based on the precipitation and temperature interpolated raster maps was initially modeled (Figs.
2,3, and 4). Because of the limitation of available European meteorological data, only one risk map of Europe was produced based on the average indices of the recent two decades. According to the results predicted by GIs, Erwinia amylovora can become potentially invasive in most parts of the central and southern European continent. Central Great Britain, Ireland, northern Portugal, northern Italy, Switzerland, southern Germany, Austria, Slovenia, Albania, western Bulgaria, and central Romania are high-risk rank regions. Great Britain, northern Spain, France, Belgium, Netherlands, western Germany, central Italy, western Czech Republic, Slovakia, Hungary, Croatia, Serbia and Montenegro,Macedonia, Romania, Bulgaria, southwestem Ukraine, and central part of Byelarus are located in
Table Risk rank of supported counties in two apple cultivation regions and assessing parameters Location Yan'an City Weinan City Xianyang City Baoji City Tongchuan City Yuncheng City Linfen City Sanmenxia City Luoyang City Qingyang City Weihai City Dalian City Pingliang City
Yantai City Zibo City Linyi City Zaozhuang City Rizhao City Qingdao City Huludao City Yingkou City Qinghuangdao City
Risk rank
Temperature during blossom period ("C)
Precipitation during blossom period (mm)
High risk
> 16.7
> 2.5
Medium risk
15.6- 16.7
2-2.5
Low risk
14.4-15.6
1.5-2
50"N
40"N Temperature durmg blossom penod ('c)
m
014.4-15.6 10"W
0"E
IO"E
20'E
30"E
= 15.6-16.7 16.7-3 1
Fig. 2 Interpolation of temperature index during the blossom period in the European continent.
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CHEN Chen et ul.
the medium-risk rank. These results correspond with field observations of the Erwinia amylovora recorded in Europe.
The same procedure was followed in China to obtain a more accurate picture. All together, 25 risk maps were calculated on the year-by-year basis, and then their av-
Fig. 3 Interpolation of precipitation index during the blossom period in the European continent.
-70"
- 60" N
-50"N
-40" N
-
Potential nsk
I&E
30' E
No nsk Low nsk
Medium nsk High nsk 0 country
Fig. 4 Potential risk of Entvnia urnylovor In European continent
92007, CAAS. All rights reserved.Publishedby Elsewer Ltd.
Potential Distribution of Alien Invasive Species and Risk Assessment: a Case Study of Envinia amylovora in China
erage helped to get an average risk map of Erwinia amylovora. By superposing the risk map on a China map (specific to counties), counties with their corresponding risk ranks were displayed clearly. It was found that the distributionof the risk area of Eminia umylovoru
11'4-E
1lf"E
693
was similar to the distribution of the apple cultivation regions, which were of great importance to fruit production. In Bohai Bay apple cultivation region, the 28 preferentially supported counties are depicted in shadow in Fig.5. It is found that these counties are
12i)"E
l2j-E
Fig. 5 Potential 25-year-average risk in Bohai Bay apple cultivation region.
Supported counue\
105"E
108"E
Fig. 6 Potential 25-year-average risk in Huangtu altiplano apple cultivation region.
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6Y 4
mostly located in the high- and moderate-riskrank areas. In the Huangtu Altiplano apple cultivation region (Fig. 6), there are 27 preferentially supported counties, which are similar to the ones depicted in the shadow in F i g 5 Similarly. it can be found that the preferentially supported counties are mostly in the high- and mediumrisk ranks, in which more than half of the preferentially supported counties are in the high-risk area rank. Only the Pingliang disrtict belongs to the low-risk rank, all the rest belongs to the medium-risk rank. The preferentially supported counties in these two regions and their corresponding risk ranks are listed in Table. The ecological environment in these two regions is fragile. There are serious losses on account of run-off soil, therefore, if the Eminia amylowm invades China, it will cause great ecological disasters as well as economic losses. Besides apple fruits, there are still a large number of host species cultivated everywhere throughout China. which are susceptible to Erwinia arnylovora, indicating a severe threat to biological diversifications.
DISCUSSION Erwinia amylovora has long been recognized as a severe invasive fruit disease in many countries throughout the world, with fruit growers frequently complaining of substantial economic losses. Through the risk analysis by GIS, it is found that a large part of China ha5 a suitable ecological environment for this disease. Considering the scale of cultivated apple areas in China, however, these results suggest significant economic impacts of Erwinia amylovora on these fruits. Thus, prevention and early detection will be the focus of most management efforts toward invasive pathogens. Once invaders establish, there is often no going back because of the difficulty of eradication. Tools are urgently needed to forecast the future invaders’ spread, and to assess the worthiness of prevention efforts (Clark et al. 2001; Leung ef al. 2002). Managers need a way to prioritize and direct prevention efforts to known invaders (van der Zanden et al. 2004). Advances are also being made to identify the troublesome invaders of the future; for example, several recent studies use a risk assessment framework to identify potential invaders (Kolar and Lodge 2002; Ricciardi and Rasmussen 1998). Risk assessment of an invasive species is generally con-
CHEN Chen et al.
ducted to inform two classes of risk management decisions: (1) those regarding the introduction of potentially invasive nonindigenous species, their vectors, or conveyances prior to establishment (leading to decisions to authorize, prohibit, or permit activities under specified conditions), and (2) decisions regarding the allocation of scarce resources for the control of established invasive species, including rapid response to emerging threats. Risk management is the process of identifying, evaluating, selecting, and implementing actions to reduce risk (Andersen et al. 2004). Although efforts have been made to describe the attributes of successful invaders and invasible ecological communities (Orians 1986), ecologists have lamented the difficulty in making quantitative predictions about invaders (Lodge 1993), and the broad-scale statistical patterns of the invaders’ success still remains pretty much in the dark. The geographical approach, outlines the potential distribution of alien species, as a first step to determine which may be potentially invasive, as well as provides guidelines to diminish future impacts in specific regions. This approach is inexpensive and based on reliable validation. This procedure can be generalized for almost any species. Likewise, this methodology can also be included in the risk analysis protocol to provide a valuable initial baseline for implementing integrated pest assessment, prevention, and management of alien species that could potentially become invasive under certain environmental conditions. To sum up, this methodology, as exemplified here, is a low-cost, robust tool, with applicability to many other pest taxa and agricultural regions worldwide.
Acknowledgements This study was supported by the National 973 Program of China (2002CB111405). We would like to thank the Archives of Center Meteorological Bureau, China, as well as the National Center of Atmospheric Research of the United States, for their generous provision of the meteorological data.
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