CHARACTERIZATION OF SYMBIOTIC MYCOFLORA OF NON NATIVE AMBROSIA BEETLES By CRAIG CHRISTOPHER BATEMAN A THESIS P RESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2014
Â© 2014 Craig Christopher Bateman
To my parents
4 ACKNOWLEDGMENTS I am greatly thankful to have received the guidance, support, time and patience of my committee chair Jiri Hulcr, and committee members Jason Smith and Matthew Smith. My committee has helped me grow as a scientist and person, while also providing welcome and enjoyment as a member of the lab and as a friend. For discussions, technical aids, and help navigating various analyses, I would like to thank the members of the Hulcr lab; Martin Kostovcik, Caroline Storer, Andrew Johnson, and Polly Harding, and members of the Forest Pathology lab; Adam Black, Tyler Dreaden, and Marc Hughes. I wo uld like to thank Martin Sigut for his help extracting fungi from the black twig borer and for help with statistical analyses . I am also thankful for the advice and help on Fusarium quarantined research facil ities, I thank Dr. Timothy Schubert. For help with beetle collections, I am thankful for Dr. Paul Kendra and Chris Gibbard. I would also like to thank collaborators Wang Bo and Wisut Sittichaya for which work overseas would have not been possible.
5 TABLE O F CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CH APTER 1 THE MYCANGIAL SYMBIONT OF THE BLACK TWIG BORER ,Xylosandrus compactus (COLEOPTERA: CURCULIONIDAE, SCOLYTINAE) IS SPATIALLY SEGREGATED. ................................ ................................ ................................ ...... 11 Introduction ................................ ................................ ................................ ............. 11 Methods ................................ ................................ ................................ .................. 14 Sampling and Isolation ................................ ................................ ..................... 14 DNA Sequence Acquisition and Phylogenetic Analysis ................................ .... 15 Statistical Analysis ................................ ................................ ............................ 17 Results ................................ ................................ ................................ .................... 17 Fungi Associated with Xylosandrus compactus ................................ ................ 17 The Two Dominant Fungal Associates are Spatially Segregated during Transport ................................ ................................ ................................ ....... 18 D iscussion ................................ ................................ ................................ .............. 19 2 FUNGI ASSOCIATED WITH EXOTIC XYLEBORINI AMBROSIA BEETLES IN FLORIDA ................................ ................................ ................................ ................ 27 Introduction ................................ ................................ ................................ ............. 27 Methods ................................ ................................ ................................ .................. 30 Beetle Collections and Fungal Isolations ................................ .......................... 30 DNA Sequence Acquisition and Analys is ................................ ......................... 31 Results ................................ ................................ ................................ .................... 32 Fungi Associated with Exotic Xyleborini ................................ ........................... 32 DNA Sequencing and Phylogenetic Analysis ................................ ................... 33 Discussion ................................ ................................ ................................ .............. 34 3 PREDICTING FUTURE INVADERS; ARE UNKNOWN PATHOGENS HIDING IN ASIA? ................................ ................................ ................................ ................. 44 Introduction ................................ ................................ ................................ ............. 44 and ................................ ................................ .......... 46 Preventing the Next Tree Epidemic ................................ ................................ .. 47 Methods ................................ ................................ ................................ .................. 49
6 Study Sites and Beetle Collection ................................ ................................ .... 49 Fungal Isolation ................................ ................................ ................................ 49 Molecular Identification and Phylogenetic Analysis ................................ .......... 50 Pathogenicity Test ................................ ................................ ............................ 52 Results ................................ ................................ ................................ .................... 53 Fungal Isolations and Identification ................................ ................................ .. 53 Pathogenicity Test ................................ ................................ ............................ 54 Discussion ................................ ................................ ................................ .............. 54 LIST OF REFERENCES ................................ ................................ ............................... 61 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 68
7 LIST OF TABLES Table page 1 1 Primers used for PCR and DNA sequencing ................................ ...................... 23 1 2 Average number of fungal coloni es from different parts of Xylosandrus compactus. ................................ ................................ ................................ ......... 23 1 3 Prevalence a of fungi isolated from different parts of Xylosandrus compactus . ... 24 1 4 Presence (+)/absence ( ) of fungi isolated from beetle galleries from thre e localities in Gainesville, FL ................................ ................................ ................. 25 2 1 Prevalence and abundance of fungi isolated from exotic Xylebor ini ................... 38 2 2 Combined reports of Xyleborini fungal symbionts in the literature and present study ................................ ................................ ................................ ................... 38 3 1 Prevalence and abundance of fungi associated with Asian bark beetles sampled. ................................ ................................ ................................ ............. 58 3 2 Mean number of weeks seedlings displayed resin production in loblolly pine genotype 1 inoculated with Asian fungi. ................................ ............................. 58 3 3 Mean number of weeks seedlings displayed resin production in loblolly pine genotype 2 inoculated with Asian fungi. ................................ ............................. 59 3 4 Mean number of weeks seedlings displayed resin production in slash pine inoculated with Asian fungi. ................................ ................................ ................ 59 3 5 Mean vertical xylem lesion length in loblolly pine genotype 1 inoculated with Asian fungi. ................................ ................................ ................................ ......... 59 3 6 Mean vertical xylem lesion length in loblolly pine genotype 2 inoculated with Asian fungi. ................................ ................................ ................................ ......... 59 3 7 Mean vertical xylem lesio n length in slash pine inoculated with Asian fungi. ...... 60 3 8 Mean vertical phloem lesion length in loblolly pine genotype 1 inoculated with Asian fungi. ................................ ................................ ................................ ......... 60 3 9 Mean vertical phloem lesion length in loblolly pine genotype 2 inoculated with Asian fungi. ................................ ................................ ................................ ......... 60 3 10 Mean vertical phloem lesion length in slash pine inoculated with Asian fungi. ... 60
8 LIST OF FIGURES Figure page 1 1 Maximum likelihood based identification of Xylosandrus compactus mycangial isolate of Ambrosiella xylebori with Raffaelea lauricola used as an outgroup. ................................ ................................ ................................ ............ 25 1 2 Principal Correspondence Analysis (PCA) ordination biplot with histogram of explained c ummulative variation. PCA biplot shows beetle parts colonized by different fungi. ................................ ................................ ................................ ..... 26 2 1 Maximum likelihood based identification of Xylosandrus amputatus mycangial isolate Ambrosiella beaveri with Microascus cirrosus used as an outgroup ................................ ................................ ................................ ............. 39 2 2 Maximum likelihood based identification of Xylosandrus amputatus mycangial isolate Ambrosiella beaveri with Raffaelea lauricola used as an o utgroup ................................ ................................ ................................ ............. 40 2 3 Maximum likelihood based identification of the Xyleborinus andrewesi mycangial isolate Raffaelea subalba with Ambrosiella xylebori used as an outgroup ................................ ................................ ................................ ............. 41 2 4 Maximum likelihood based identification of the Xyleborinus andrewesi mycangial isolate Raffaelea subalba with Ambrosiella xylebori used as an outgroup ................................ ................................ ................................ ............. 42 2 5 Cladogram of main Xyleborini clades corresponding to myangium type and patterns in symbiont communnities inferred from literature and the present study. ................................ ................................ ................................ .................. 43 3 1 Symptoms of Ophiostom a ips on Pinus taeda seedling stems during disease development (left) and after destructive sampling (lateral bisection, right). ........ 58
9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science CHARACTERIZATION OF SYMBIOTIC MYCOFLORA OF NON NATIVE AMBROSIA BEETLES By Craig Christopher Bateman August 2014 Chair: Jiri Hulcr Co chair: Jason Smith Major: Forest Re sources and Conservation In virtually every forest habitat, ambrosia beetles (Coleoptera: Curculionidae: Scolytinae, Platypodinae) plant and maintain symbiotic fungus g ardens inside dead or dying trees . Some non native ambrosia beetles aggressively attack live trees and can damage tree crops, lumber, and native woody plant taxa by in troducing phytopathogenic ambrosia fungi. Non native ambrosia beetle introductions have become increasingly frequent in the United States, yet there is almost nothing known abo ut their fungal symbionts. To determine the identity and diversity of symbiotic ambrosia fungi, exotic beetles were collected in Florida and their fungi were isolated. Results support the hypothesis that some beetles carry highly specific monocultures of f ungi, while others have a diverse community of symbionts that may be traded with other ambrosia beetles. These results are now being used to test hypotheses and models explaining the evolution of pathogenicity within ambrosia fungi and invasion ability wit hin beetle fungus complexes. Pathogenicity displayed by ambrosia fungi was also investigated in Asia, where symbiotic fungi of beetles were isolated and evaluated for pathogenicity to American
10 trees to determine if new pathogen invasions can be effectivel y predicted and prevented. The fungal isolates were tested for ability to cause disease in the two most economically important pines in the southeast U.S. ( Pinus taeda and P. elliottii) by inoculation in a quarantine facility. The most virulent beetle asso ciated fungus tested was Ophiostoma ips ; an established pathogen of pines. This project demonstrates the feasibility of assessing the invasion potential of not yet established insects and fungi and will offer a route for regulatory agencies to effectively protect pines, one of the most valuable commodities in the southeast.
11 CHAPTER 1 THE MYCANGIAL SYMBIONT OF THE BLACK TWIG BORER , Xylosandrus compactus (COLEOPTERA: CURCULIONIDAE, SCOLYTINAE) IS SPATIALLY SEGREGATED. Introduction Bark and ambrosia beetles (C oleoptera: Curculionidae, Scolytinae) are normally widespread colonizers of dead or dying wood, but some species attack apparently healthy trees (Kuhnholz et al. 2001, Hulcr and Dunn 2011). This behavior is most common in invasive ambrosia beetle species a nd poses serious risks to tree crops, lumber industries, landscape ornamentals and native woody plants through structural damage as well as the spread of plant pathogens. Although ambrosia fungi often play a greater role in contributing to tree death or da mage than the beetle, traditionally the fungal symbionts have been understudied and most remain undescribed. Information on identity of these fungi is critical for understanding the composition and function of beetle symbiont communities. The specificity a nd promiscuity of beetle fungus communities may determine the evolution of pathogenicity and invasion ability (Carrillo et al. 2013). This idea requires investigation in order to develop methods of control that reduce the economic and ecological impacts of these invasive symbiont complexes. Xylosandrus compactus , the black twig borer, is one of the most studied ambrosia beetle species worldwide due to its long history as a pest of healthy trees (Daehler and Dudley 2002). The female bores into and cultivates symbiotic fungal gardens in the pith of young stems on apparently healthy trees, causing death from the terminal ends of the branch to the initial entrance hole (Hara and Beardsley Jr 1976, Wood 1982). Well over 200 tree species are recorded as hosts to X . compactus (Ngoan et al. 1976). Many commercial crops are impacted, with substantial losses recorded in avocado (McClanahan 1951), mango, tea (Kaneko et al. 1965), coffee (Brader 1964),
12 and cocoa (Hara and Beardsley Jr 1976). Nurseries can be heavily impa cted, mostly by aesthetic damage to ornamentals and orchids (Dekle and Kuitert 1968, Ngoan et al. 1976). In island ecosystems such as Hawaii, endangered plants are threatened by this exotic pest (Nishida and Evenhuis 2000). Despite the diverse and far reac hing impacts of X. compactus , many basic characteristics of this species remain unknown. This is especially true concerning the identity and stability of its fungal symbiont community. Many different fungi have been described as associates of X. compactus ; but three have been reported most consistently: Ambrosiella xylebori , A. macrospora , and Fusarium solani (Brader 1964, Arx and Hennebert 1965, Batra 1967, Bhat and Sreedharan 1988). A. xylebori has also been described in association with other beetle spec ies, including taxa that are congeneric (e.g., Xylosandrus crassiusculus (Gebhardt et al. 2005)) and those that are more distantly related (e.g., Corthylus columbianus (Batra 1967)). Morphological species recognition frequently fails within Ambrosiella and Fusarium due to their phenotypic similarity. Thus, the reports of Ambrosiella macrospora from a broad range of beetles, including Ips acuminatus infesting Pinus spp. in Europe (Francke Grosmann 1952, Batra 1967) and X. compactus (Muthappa and Venkatasubb aiah 1981), needs to be confirmed using DNA sequence data. Fusarium solani is a name given to a complex of over 45 morphologically cryptic species (O'Donnell et al. 2008). Members of the F. solani complex (hereafter referred to as the FSSC) have been repo rted in association with many distantly related beetles, including Xyleborus ferrugineus (Baker and Norris 1968), Hypothenemus hampei (Rojas and Morales Ramos 1999), Scolytodes unipunctatus (Kolarik and Hulcr 2008), Xylosandrus compactus (Ngoan et al. 1976 ) and several other genera (Hulcr and
13 Cognato 2010). A clade of true ambrosia fungi was recently discovered within the FSSC that appear to have coevolved with ambrosia beetles (the Ambrosia Fusarium Clade (AFC)), while many other cases of Fusarium reported from ambrosia beetles are likely environmental contaminants rather than true symbionts (Kasson et al. 2013). This finding raises the question whether Fusarium species reported from X. compactus belong to the AFC clade, represent a new ambrosial lineage, o r are environmental contaminants. In order to characterize the symbiosis between X. compactus and its fungal associates for use in future research on the symbiosis, this study was initiated to: 1. Quantitatively characterize the fungal community in terms of d iversity and abundance distribution. 2. Determine whether different fungal symbionts co occur in beetle mycangia during transport or are spatially separated to different beetle body parts
14 Methods Sampling and Isolation Fungi were isolated from liv e adult female beetles and infested plant material during April May of 2013. Beetles in flight were collected from ethanol baited traps at three localities in Gainesville, Florida: NW 12th Avenue (GPS 29Â° 39' 47.48", 82Â° 20' 2.92"), Northeast Park (GPS 29 Â° 39' 53.32", 82Â° 19' 15.88"), and McCarty Woods Park (GPS 29Â° 38' 43.16", 82Â° 20' 42.37"). Five adult X. compactus beetles from each site were used for fungal isolation. Beetles captured in flight were stored on lightly moistened paper tissue at 15Â° C for up to three days prior to fungus extraction. Only females were examined because Xyleborini males lack mycangia; they are flightless and do not leave their natal galleries to establish new colonies. Fungi were isolated from four locations on the beetle: the surface, mycangium, and from within the anterior (head and pronotum) and posterior (mesonotum to abdomen) halves of the beetle. The surface of adult females was washed by vortexing in a 1 mL sterile solution of 1% Tween 80 (Sigma Chemical Co, St. Loui s, MO, USA) and phosphate buffer saline (PBS) and then was serially diluted prior to plating. Following the wash, beetles were vortexed at 2100 rpm for 15 seconds in 1mL sterile PBS and allowed to dry on tissue paper. Live beetles were then secured onto pa raffin wax using minuten pins (Bioquip, Rancho Dominguez, CA). Minuten pins were used to pry the pronotum away from the mesonotum, revealing the mycangium (Francke 1967). Under 60X magnification (Fisher Scientific Stereomaster), the fungal mass was transfe rred into a 2 mL microcentrifuge tube containing 0.5 mL PBS using a flame sterilized 000 insect pin (Bioquip). Beetles were aseptically severed between pronotum and mesonotum. Each half of the beetle was then crushed in separate
15 microcentrifuge tubes conta ining .5 or 1 mL sterile PBS using plastic pestles (Fisher Scientific, Suwanee, GA). 1/10, 1/100, and 1/1000 serial dilutions were made from each sample (i.e., surface wash, head, mycangium and abdomen). Dilutions were plated on Potato Dextrose Agar (Difco Labs, Detroit, MI) amended with 1.4% additional agar (Fisher Scientific, Fairlawn, NJ). Plates were stored in an incubator in the dark at 25Â° C for up to two weeks. Fungal colony forming units (CFUs) were morphotyped and relative abundances calculated. Pl ates were monitored every 2 3 days during the two week incubation and photographed to ensure consistent assignment of morphotypes. Morphotype designations were confirmed by retrospective comparisons of pure cultures and by sequencing up to three portions o f the nuclear ribosomal DNA (rDNA) and four protein encoding genes. DNA Sequence Acquisition and Phylogenetic Analysis Pure cultures between 1 2 weeks old were used for DNA extraction. Mycelium (10 20 Âµl) was added to 20 uL of Sigma Aldrich Extraction Solu tion (Extract N Amp, St. Louis, MO) in 0.25 mL PCR tubes, which were then incubated in a thermocycler (Eppendorf Mastercycler) at 96Â° C for 10 minutes. After incubation, 20 ÂµL of 3% BSA (Fermentas) was added to each tube, vortexed for 5 sec and then centri fuged at 2000 rpms for 30 seconds. The upper half of this solution was used as genomic DNA template for PCR. Partial sequences were obtained from three nuclear ribosomal RNA (rDNA) encoding regions, and portions of four protein coding genes, from up to fi ve isolates of each morphotype. A three locus typing scheme, employing portions of the ITS+LSU
16 rDNA, EF et al. 2008), was used to identify a Fusarium isolate as a novel species within the F. solani species complex, which was designat ed FSSC 45 a. Arabic numbers and lowercase Latin letters are used to identify, respectively, phylospecies and haplotypes within the FSSC. Isolate Fusarium sp. FSSC 45 a was accessioned in the ARS Culture Collection as NRRL 62797 where it is available upo n request ( http://nrrl.ncaur.usda.gov/ ). PCR reactions contained a final volume of 25 ÂµL: 1 ÂµL of template DNA, 1 ÂµL of forward and reverse primer (10 ÂµM), 0.125 Âµl of Taq (TakaraÂ®), 2.5 ÂµL PCR buffer (15 mM MgCl 2), 2 ÂµL dNTP mix (2.5 mM each dNTP), and 20 uL sterile water. PCR and sequencing primers are listed in Table 1 1 . PCR products were purified using Exosap were performed i n an Eppendorf Mastercycler Pro following published cycling parameters (Kim et al. 2004). DNA sequencing was performed on an ABI PRISM 377XL or 3130XL automated DNA sequencer by the Interdisciplinary Center for Biotechnology Research, University of Florida , Gainesville. Forward and reverse sequences were assembled into contigs in Geneious (Version 7.0). BLAST queries of the NCBI GenBank database were performed with each sequence to identify the fungi that were cultured. Final taxonomic identities were as signed by phylogenetic comparisons to congeneric sequences available in Genbank. Maximum likelihood phylogenetic analyses were performed using PhyML (Guindon et al. 2010) with 1,000 bootstrap replicates and the TrNef+I model of substitution, which was chos en by jModelTest (Guindon and Gascuel 2003, Darriba et al. 2012).
17 Statistical Analysis Principal component analysis (PCA) in CANOCO 5.0 (Ter Braak and Smilauer 2012) was used to describe fungal community structure. The twelve most commonly isol ated species, which comprised 53 samples, were included in the PCA. Four species found in fewer than five of the beetles sampled (i.e., Epicoccum nigrum , Mycosphaerella sp., Penicillium communae ) were excluded from the analysis. The effect of two variables on fungal species distribution was explored: (1) beetle part as a factor with 4 levels (head, abdomen, mycangium, surface wash) and (2) individual beetles. These 2003). The factor of beetle individual did not add significant explanatory power to the analysis (Forward step selection analysis, p = 0.142) and was therefore excluded from the final analysis. Results Fungi Associated with Xylosandrus compactus A total o f 14 fungal morphotypes were isolated from adult X. compactus females captured in flight in north central Florida ( Table 1 2 , 1 3, and 1 4 ) . Morphotypes could not be accurately placed at a species level within the genus Fusarium , which was the most prevale nt morphotype. The Fusarium morphotype was comprised of at least three different members of Fusarium solani species complex (FSSC) based on phylogenetic analysis of a three locus dataset (O'Donnell et al. 2008). Fusarium was recovered from 93.3% of beetles sampled (mean CFUs per beetle = 11,131, sd = 19,244, Nbeetles = 15). The second most common fungus isolated was identified as Ambrosiella xylebori based on a 100% match to SSU and LSU rDNA sequence data from the holotype strain of A. xylebori CBS 110.61 ( Fi gure 1 1, GenBank accessions AY858659 and EU984294,
18 respectively). ITS sequences for this isolate were not available in public databases, but were generated in this study and deposited in Genbank. Ambrosiella xylebori was isolated from 73.3% of all adult beetles sam pled (mean CFU = 12,347, sd = 25,835, Nbeetles = 15). A yeast species in the genus Filobasidium was recovered from 66.7% of the beetles (mean = 8,934, sd = 25,489, Nbeetles = 15), and Acremonium from 53.3% of the beetles (mean = 1,024, sd = 2,968, Nbeetle s = 15). CFU counts of these two fungi were appreciable but their association with specific body parts was inconsistent (Table s 1 2 and 1 3 ). The 10 remaining fungal species were isolated from less than 50% of the beetles (Table 1 2 and 1 3). DNA typing of fungi from galleries provided qualitative confirmation that the most frequent beetle associates were also present in active galleries (Table 1 4). The Two Dominant Fungal Associates are Spatially Segrega ted during Transport The PCA suggested that the two most common fungi isolated differ significantly in their association with beetle body parts (Figure 1 2 ). Specifically, there appears to be a significant connection between Ambrosiella and beetle mycangium, and between Fusarium and beetle surface. Also, P C1 and PC2 axes separated samples from surface+abdomen in the opposite direction from head+mycangium, suggesting that different regions of the body (surface+abdomen, head+mycangium) each shares distinct communities of fungi during beetle migration. The fir st two axes captured 51.7% of the variability in the species data, (PC1: 31.9%, PC2: 19.8%).
19 Discussion Results of this study established that fungi in both the genera Ambrosiella and Fusarium are the two most common fungal associates of Xylosandrus comp actus in north central Florida. Ambrosiella was isolated from two thirds of the mycangia sampled, while Fusarium was recovered primarily from the body surface and to a lesser extent from beetle abdomens and mycangia (Table 1 2 and 1 3). Although difficulti es in assigning morphotypes limited resolution of symbiont specificity to a genus level association, the results nonetheless elucidate previously unknown characteristics of the symbiosis. This is the first record of an ambrosia beetle that is associated wi th spatially segregated fungi. This study was also the first to demonstrate that Fusarium species associated with X. compactus are not likely to be a part of the Ambrosia Fusarium Clade (AFC, Kasson et al. 2013), and that X. compactus is the first x ylebori ne ambrosia beetle consistently associated with Fusarium species that is not a member of the AFC. Although our samples were limited to Florida, reports of Ambrosiella and Fusarium associated with X. compactus from Hawaii (Daehler and Dudley 2002, Kuo 2010) and Japan (Hayato 2007) suggest these associations may be distributed worldwide. The role that Fusarium plays in the ecology and life history of X. compactus , is currently unknown but deserves further study. Since it is carried on the surface and probabl y in the gut, but much less frequently in the mycangium, we speculate that the association is probably evolutionary recent and less specific than that between beetles and coevolved nutritional symbionts. Members of the genus Fusarium were also abundant in the gallery. During the course of this study, Fusarium spp. were typically isolated from heavily stained areas around galleries in twigs attacked by X. compactus (Table 1 4). Two hypotheses may explain this pattern. (1) Fusarium spp. are
20 opportunist s that sporulate prolifically and is competitive in the gallery. (2) Fusarium spp. are so prevalent because they are phytopathogen s and suppress defense mechanisms in the twig . The difficulty of distinguishing phoretic opportunists from beneficial mutualists has been discussed extensively within the scolytine fungus literature (Six and Wingfield 2011). Our discovery that Ambrosiella is the most prevalent fungus in the mycangium of X. compactus suggests they are engaged in a close knit nutritional symbiosis. This f inding appears to corroborate reports of this association from around the world (Daehler and Dudley 2002, Hayato 2007, (Muthappa and Venkatasubbaiah 1981)), including the original description of Ambrosiella from X. compactus infesting coffee in Ivory Coast (Brader 1964). Portions of the partial SSU and LSU rDNA sequences of A. xylebori in Florida were identical to those from the holotype strain (CBS 110.61). At present, broader geographic taxon sampling and more informative marker loci are needed to underst and exactly where the symbiosis originated and whether symbiont fidelity is maintained worldwide. It is unclear why Ambrosiella xylebori was not recovered from 26.7% of the X. compactus sampled. The absence of Ambrosiella from some beetle samples may be a methodological artifact or due to interactions between the mycangium and fungus. Mycangia are thought to provide important nutrients for growth and storage of fungi during transport to new substrates (Francke Grosmann 1967). We observed that mycangia of b eetles taken from galleries always appeared empty, while those caught in flight typically appeared filled with fungus. Fungi inhabiting the mycangium may need time to grow sufficiently, or rely on cues from the beetle before inoculation and growth in
21 a new gallery (Kinuura 1995). The beetles that did not yield Ambrosiella may have been captured before the symbiotic fungus had sufficiently colonized the mycangium. The high variability in past studies in reporting Ambrosiella from X. compactus may be due to i nconsistent methodology, or due to development induced variation in symbiont abundance. A yeast in the genus Filobasidium (Kwon Chung 1977, Pan et al. 2011) was also recovered from more than half of the beetles as well as from a gallery. Laboratory reari ng experiments are needed to assess what role, if any, F. uiguttatum , Acremonium sp. and the 10 other less frequently sampled fungi play in the life history of X. compactus . Our study revealed that isolation from different X. compactus body parts yielded c ompletely different symbiont communities. However, the dominant fungi from all body parts were also found in beetle galleries. This finding suggests that mechanisms may exist that restrict these symbionts to different parts of the beetle body, or that they are adapted for transport on beetles different ly . For example, the abundant Fusarium spores may easily adhere to the beetle surface and/or survive passage through the gut, while Ambrosiella appears to be selected for or is competitive within the mycangium . Secretions in the mycangium may provide an advantage to specialized coevolved symbionts (i.e., Ambrosiella ). One of the goals of this study was to establish a reliable approach to culture based analyses of ambrosia beetle symbionts that considers insect anatomical and ontogenetic complexity. Based on these results, the traditional approach of processing whole beetles may not be appropriate for capturing the fine scale community structure
22 of the symbionts. This and many such beetle fungal symbioses are ec ologically and economically destructive, and need to be studied carefully to elucidate theoretical and practical aspects of their biology. Future studies that focus on, the rapid emergence of fungal pathogenicity and virulence in formerly har mless ambrosi a beetles are needed to devise effective methods for the detection, control and eradication of these exotic pests.
23 Table 1 1. Primers used for PCR and DNA sequencing Locus Gene product Primer name Primer sequence (5' 3') a PCR S b Reference NS4 CTTCCGTCAATTCCTTTAAG (White et al. 1990) ITS rDNA Internal transcribed spacer ITS1 TCCGTAGGTGAACCTGCGG (White et al. 1990) ITS4 TCCTCCGCTTATTGATATGC (White et al. 1990) LSU rDNA Nuclear ribosomal large subunit (28S) NL1 CTTGGTCATTTAGAGGAAGTAA (Vilgalys and Hester 1990, O'Donnell 1992) LR3 CCGTGTTTCAAGACGGG (Vilgalys and Hester 1990) LROR ACCCGCTGAACTTAAGC (Vilgalys and Hester 1990) EF Translation elongation EF1 ATGGGTAAGGARGACAAGAC et al. 1998) EF2 GGARGTACCAGTSATCATG et al. 1998) EF3 GTAAGGAGGASAAGACTCACC (O'Donnell et al. 2008) EF22T AGGAACCCTTACCGAGCTC et al. 1998) RPB1 RNA polymerase largest subunit Fa CAYAARGARTCYATGATGGGWC ( Hofstetter et al. 2007) G2R GTCATYTGDGTDGCDGGYTCDCC (O'Donnell et al. 2010) R8 CAATGAGACCTTCTCGACCAGC (O'Donnell et al. 2010) F5 ATGGGTATYGTCCAGGAYTC ( O'Donnell et al. 2010) F6 CTGCTGGTGGTATCATTCACG ( O'Donnell et al. 2010) F7 CRACACAGAAGAGTTTGAAGG (O'Donnell et al. 2010) F8 TTCTTCCACGCCATGGCTGGTCG (O'Donnell et al. 2010) R9 TCARGCCCATGCGAGAGTTGTC (O'Donnell et al. 2010) RPB2 RNA polymerase second largest subunit 5f2 GGGGWGAYCAGAAGAAGGC (Reeb et al. 2004) 7cr CCCATRGCTTGYTTRCCCAT (Liu and Hall 2004) 7cf ATGGGYAARCAAGCYATGG (Liu and Hall 2004) 11ar GCRTGGATCTTRTCRTCSACC (Liu and Hall 2004) benA tubulin T1 AACATGCGTGAGATTGTAAGT (O'Donnell and Cige lnik 1997) BT2B ACCCTCAGTGTAGTGACCCTTGGC (Glass and Do naldson 1995) a D = A, G or T; R = A or G; S = C or G; W = A or T; Y = C or T. b S= used in sequencing
24 Table 1 2 . Average number of fungal colonies from different parts of Xylosandrus compactus. Species Surface Head Mycangium Abdomen Acremonium sp . 177.4 206.7 133.3 281.3 Ambrosiella spp. 0 333.4 1944.4 2252.5 Cladosporium sp. 163.3 124 63.3 257.3 Epicoccum nigrum 7.3 66.7 0 0 Filobasidium sp. 5415.6 1372.6 89.3 70.3 Fusarium spp. 2565 381.3 780.6 1206 Fusarium verticillioides 74.7 0 0 6.7 Meira sp. 1333 0 0 0 Mycosphaerella sp . 0 26.7 0 0 Penicilium minioluteum 161 66.7 0 6.7 Penicillium communae 0 13.3 0 0 Pestalotiopsis sp. 0.66 108.6 3691 80 Phaeoacremonium scolyti 0 0 0 146.7 Phialemonium sp. 18129 7491 4933 11621 Table 1 3 . P revalence a of fungi isolated from different parts of Xylosandrus compactus . Species Surface Head Mycangium Abdomen Total Prevalence Acremonium sp. 46.7 13.3 6.7 26.7 53.3 Ambrosiella spp. 0 53.3 66.7 26.7 73.3 Cladosporium sp. 26.7 33.3 26.7 26.7 40 Epicoccum nigrum 13.3 6.7 0 0 20 Filobasidium sp. 40 33.3 33.3 20.0 73.3 Fusarium spp. 80 33.3 20 66.7 93.3 Fusarium verticillioides 20 0 0 6.7 20 Meira sp . 6.7 0 0 0 6.7 Mycosphaerella sp. 0 6.7 0 0 6.7 Penicilium minioluteum 13.3 6.7 0 6.7 20 Peni cillium communae 0 6.7 0 0 6.7 Pestalotiopsis sp . 6.7 26.7 13.3 13.3 46.7 Phaeoacremonium scolyti 0 0 0 6.7 6.7 Phialemonium sp. 20.0 13.3 6.7 26.7 13.3 a Percent samples yielding fungus species
25 Table 1 4 . Presence (+)/absence ( ) of fungi isola ted from beetle galleries from three localities in Gainesville, FL: NW = NW 12th Avenue, NP = Northeast Park, MWP = McCarty Woods Park, only species isolated at least once are included. Species NW NP MWP Ambrosiella spp. + + Filobasidium sp. + Fu sarium spp. + + Fusarium verticillioides + + Phialemonium sp. + Figure 1 1 . Maximum likelihood based identification of Xylosandrus compactus mycangial isolate of Ambrosiella xylebori with Raffaelea lauricola used as an outgroup . Ingroup seque nces are from members of the genera Ceratocystis and Ambrosiella (Microascales) Relationships were inferred from combined SSU+LSU rDNA sequence data. Numbers next to nodes are maximum likelihood bootstrap values based on 1,000 bootstrap replicates .
26 Figur e 1 2 . Principal Correspondence Analysis (PCA) ordination biplot with histogram of explained cummulative variation. PCA biplot shows beetle parts colonized by different fungi.
27 CHAPTER 2 FUNGI ASSOCIATED WITH EXOTIC XYLEBORINI AMBROSIA BEETLES IN FLORID A Introduction In recent years, exotic wo od boring beetles have become som e of the most common and the most economically and ecologically detrimental insects being introduced into the United States. Included in some of these groups of invasive beetles are ambrosia beetles (Coleoptera: Curculionidae, Scolytinae), which are commonly transported across the globe and are more likely than native beetles to cause harm to naÃ¯ve forest ecosystems (Hulcr & Dunn 2011). Fungi associated with ambrosia beetles are also likely to be introduced with the arrival of each new beetle, but unfortunately most of these fungi remain mostly undetected and undescribed. Most scolytine beetles exist in some kind of nutritional relationship with fungi (Batra 1963, Beaver 1989). In ambr osia beetles and fungi, the association is obligate. Larvae and adult beetles must consume fungi to survive, and in turn the beetles relocate their fungal partners to new hosts. Most ambrosia fungi are comprised of the anamorphic ascomycete genera Ambrosie lla , Raffaelea , Fusarium , Geosmithia , and Dryadomyces (Batra 1963, Harrington et al. 2010, Kasson et al. 2013). An earlier hypothesis suggests that fungal symbiont taxa are highly specific and coevolved partners of beetles, with only one fungus per beetle (Francke Grosmann 1967, Mueller 2005). More detailed analyses indicate that many ambrosia beetles have a community of symbionts, and that fungal symbionts can be lost or incorporated from the environment (Batra 1966, Carrillo et al 2013, Kostovcik et al. i n pre ss ). Some ambrosia beetles have been recorded to share a fungal symbiont. In some instances, this occurs through mycokleptism (Hulcr and Cognato 2010). In other cases, it may be the fungus
28 or beetle that initiates the new relationship, and the mechani sms behind this are unknown. Either organism may be influenced to initiate new symbiotic relationships depending on many temporal and spatial conditions in which the association exists. This could lead to a varyin g community of fungal symbionts, especially in beetles that have broad distributions. To understand this process, the symbionts of many exotic ambrosia beetles in the United States require investigation. The beetles included in this study do not form an exhaustive list of exotic ambros ia beetles in the United States, but provide a snapshot of diversity, an d from multiple clades, of exotic beetles already established. Many exotic ambrosia beetles continue to enter the United States each year and for most of these species there are no data on their ec ological role or their symbiotic fungi in the non native environment. No fungal associates have yet been recorded from D ryoxylon onoharaensum , which has been observed attacking Acer (Bright and Rabaglia 1999) and Populus spp. (Ghandi et al. 2010), but has caused very minimal damage since its discovery in 1990 (Atkinson et al. 1990). Xylosandrus amputatus is another beetle that is not yet known to attack hea lthy native trees in the U.S.; its fungal associates remain unknown ( Kajimura 1998). Harringto n (2014) reported A. beaveri , the symbiont of C. mutilatus (another recently exotic ambrosia beetle in the U.S., Six et al. 2009), to be growing inside the galleries of X. amputatus Another As ian ambrosia beetle, Xyleborinus andrewesi , was first detected in North America in 2009. This beetle has not yet been found in live trees in the U.S., and its associated fungi are unknown (Okins and Thomas 2009). These two beetles ( X.
29 amputatus and X. andr ewesi ) are relatively recent introductions, so their impacts thus far are uncertain. Comparatively, the ambrosia beetle Cyclorhipidion bodoanum has been present in the U.S. for a much longer period (Wood 1982). Although C. bodoanum seems to prefer dead or dying trees like most ambrosia beetles, it has been implicated as a possible vector of the oak pathogen Phytopthora ramorum (McPher son et al 2010). McPherson (2010) identified Hypocrea lixii, Mucor racemosus f. racemosus, Trametes viride, Emericello psis sp., Ophiostoma sp., Pleosporaceae sp. and Trichoderma sp. as possible associates of C. bodoanum (McPherson et al. 2013). The wide variety and inconsistent association of these fungi is likely due to the methods of this study. Entire beetles were crus hed and plated, which has much greater potential to yield a mix of saprobic contaminants, opportunists, and endosymbionts. This hypothesis is supported by the fact that H. lixii and M. racemosus were also isolated from sapwood that was not colonized by bee tles. Trametes fungi are white rotting wood decay fungi which have no known anamorphs and unlikely symbionts of ambrosia beetles. T r ichoderma spp. are common fungal contaminants in all environmental samples. The remaining fungal species isolated could not be described to the species level. With the exception of the Ophiostoma sp ., all other fungi isolated are unlikely nutritional ambrosia symbionts. It is especially likely that this Ophiostoma sp. is the primary symbiont, since Ophiostoma stenoceras has bee n reported as a symbiont of C. bodoanum in an earlier study (Gebhardt et al. 2005). As evident from the numerous ambrosia beetle introductions into the U.S., some beetles are able to become widespread or attack living trees, while others are not. A
30 greate r understanding of the diversity and specificity of their symbiotic fungi will help elucidate mechanisms that govern invasion and pathogen success. These studies are critical because new, potentially dangerous exotic beetles continue to enter the country a nd old introductions continue to degrade native ecological and agricultural systems. Methods Beetle Collections and Fungal Isolations Fungi were isolated from living, adult foundress female beetles caught in flight using ethanol or freshly cut wood as lure s. Beetle dissections took place under a dissection microscope in an ethanol sterilized environ ment . Prior to beetle dissection, all beetles were individually surface washed in a 1 mL sterile solution of 1% Tween 80 (Sigma Chemical Co, St. Louis, MO, USA) and PBS, which was then was serially diluted prior to plating. For direct isolation of fungi from beetle mycangia, different dissection procedures were performed on all specimens depending on the location of the mycangium inside the different beetle specie s. Beetles with mycangia that were not known ( Dryoxylon onoharaensum ) or beetles with mandibular mycangia ( Euwallacea spp.) were aseptically separated into three parts using a scalpel prior to maceration and dilution: head, thorax, and abdomen. Beetles wit h mesonotal mycangia ( Xylosandrus amputatus ) were fixed onto paraffin wax using sterilized 000 insect pins so that the pronotum could be pried away from the abdomen. Fungi were then directly transferred from the mesonotal mycangium to 1 mL of sterile PBS p rior to serial dilution. The head+pronotum and abdomen (elytra removed) were also macerated and serially diluted. Beetles inferred to have metano t al mycangia ( Xyleborinus andrewesi ( Francke Grosmann 1967 , Beiderman n et al. 2013 )), were aseptically sectione d into three parts using a sterile scalpel: head+pronotum, mesonotum+metanotum, and abdomen.
31 Serial dilutions of 1/10, 1/100, and 1/1000 were made from each sample (location of beetle body). Dilutions were plated on Potato Dextrose Agar amended with 1.4% a dditional agar. After isolation and dilution of fungi from beetles, fungi were stored in an incubator in the dark at 25Â° C for up to two weeks to allow for elucidation of colony characteristics. Morphotypes were assigned based on macromorphology (ie , color , size comparison/growth rate, texture) for all fungal colony forming units (CFUs) occurring in more than one sample. Plates were monitored every 2 3 days during the two week incubation and photographed to ensure consistent assignment of morphotypes. Morph otype designations were confirmed by retrospective comparisons of pure cultures and by sequencing portions of the nuclear ribosomal DNA (rDNA). DNA Sequence Acquisition and Analysis Mycelia from 1 2 week old pure cultures were used for DNA extraction. 10 2 0 Âµl of mycelium was added to 20 uL of Sigma Aldrich Extraction Solution (Extract N Amp, St. Louis, MO) in 0.25 mL PCR tubes, which were then incubated (Eppendorf Mastercycler) at 96Â° C for 10 minutes. After incubation, 20 ÂµL of 3% BSA (Fermentas) was adde d to each tube, vortexed for 5 seconds and then centrifuged at 2000 rpms for 30 seconds. The upper half of this solution was used as genomic DNA template for PCR. PCR reactions contained a final volume of 25 ÂµL: 1 ÂµL of template DNA, 1 ÂµL of forward and r everse primer (10 ÂµM), 0.125 Âµl of Taq (TakaraÂ®), 2.5 ÂµL PCR buffer (15 mM MgCl2), 2 ÂµL dNTP mix (2.5 mM each dNTP), and 20 uL sterile water. PCR and sequencing primers are listed in Table 1 1. PCR products were purified using Exosap IT, following the manu
32 were performed in an Eppendorf Mastercycler Pro following published cycling parameters (Kim et al. 2004). DNA sequencing was performed on an ABI PRISM 377XL or 3130XL automated DNA sequencer by the Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville. Forward and reverse sequences were assembled into contigs in Geneious (Version 7.0). Partial sequences were obtained from up to three nuclear ribosomal RNA (rDNA) encoding regions and up to five isolates per morphotype. BLAST queries of the NCBI GenBank database were performed with each sequence to identify the fungi that were cultured. Final taxonomic identities were assigned by phylogenetic comparisons to conge neric sequences available in Genbank. Maximum likelihood (ML) phylogenetic analyses for fungi associated with Xylosandrus amputatus and Xyleborinus andrewesi were performed using PhyML (Guindon et al. 2010) with 1,000 bootstrap replicates. Analyses perform ed on fungi isolated from X. amputatus utilized a TIM2ef+I substitution model for b tubulin trees, and a TrNef+G model for LSU trees. The TrN+G model of substitution was used for fungi associated with X. andrewesi . All substitution models used in ML analys es were chosen by jModelTest (Guindon and Gascuel 2003, Darriba et al. 2012). Results Fungi Associated with Exotic Xyleborini Isolations of fungi from the mycangia of four species of exotic ambrosia beetles yielded one highly abundant and prevalent filamen tous fungus morphotype with each ambrosia beetle species sampled. No consistent filamentous or yeast fungi were isolated from Dryoxylon onorenhaesum . Seven morphotypes of filamentous fungi were isolated from Xylosandrus amputataus , but only one morphotype was recovered from
33 both adult beetle mycangia and a gallery, and in high frequency and abundance (Figure 2 1). Similarly, six morphotypes were isolated from X. andrewesi , but only one was domen, where symbionts have been reported to be transported in this beetle genus ( Francke Grosmann 1967, Beidermann et al. 2013). In all Euwallacea validus beetles sampled, three morphotypes of filamentous fungi were recovered, with two being found on 100% of beetles sampled. Euwallacea interjectus specimens sampled also yielded three filamentous fungal morphotypes, with one morphotype recovered from all beetles. DNA Sequencing and Phylogenetic Analysis Blast queries of the NCBI GenBank database indicated that partial sequences tubulin gene from the most abundant filamentous fungus morphotype associated with Xylosandrus amputatus was most similar to Ambrosiella beaveri CBS 121751 with 99% similarity in o verlapping regions ( Genbank accessions EU825650 , EU825656). After alignment with all closely related Ambrosiella and Ceratocystis tubulin sequences indicated A. beaveri and the fungus isolate from X. amputatus f ormed a monophyletic group (Figures 2 2, 2 3). The most abundant morphotype isolated from Xyleborinus andrewesi was found to be most similar to Raffaelea subalba (isolate C2224 , GenBank accession EU177467 ) based on BLAST queries using partial sequences of LSU rDNA. Sequence data from other loci was unavailable for R. subalba in GenBank. Maximum likelihood phylogenetic analysis using LSU sequences revealed the isolate to form a monophyletic group with Raffaelea subalba (Figure 2 4).
34 Two different filamentou s fungi isolated from Euwallacea interjectus and E. validus were found to be members of the Fusarium solani species complex (FSSC) and were subsequently found to be part of a novel clade of ambrosia fungi within the FSSC by congruence between all three met hods of phylogenetic inference using a four locus data set (described in Kasson et al. 2013). In addition to a novel Fusarium sp. being described from E. validus , another filamentous fungus isolated from 100% of beetles sampled was identified. Initial BLA ST queries of LSU sequence data indicated this second filamentous fungus to be 99% similar to Raffaelea subfusca (isolate C2335, GenBank accession EU177450 ) in overlapping regions. Discussion Fungal isolations from beetle mycangia and identification of co nsistent fungal associates through sequencing and phylogenetic analyses performed here have helped to identify symbiotic fungi associated with four exotic ambrosia beetles in the United States. Phylogenetic analyses of LSU and B tubulin genes indicate that Ambrosiella beaveri is strongly associated with Xylosandrus amputatus , Raffaelea subalba with Xyleborinus andrewesi , and R. subfusca and Fusarium sp. with Euwallacea validus . It is interesting that each of these three fungi has been previously reported i n association with other ambrosia beetle species, especially in the case of Xylosandrus amputatus . All beetles within the genus Xylosandrus have been previously appeared to have strict symbioses with only one Ambrosiella species , which is apparently not ma intained in symbiosis with any other beetle species. However, in addition to A. beaveri being reported as a symbiont of X. amputatus i n the present study, Six (2009) reported A. beaveri to be dominant fungus found in the mycangia of Cnestus mutilatus .
35 If A mbrosiella species are indeed specific to only one beetle species, it is possible that A. beaveri is associated with only one of beetle species in Asia where both beetles are native, and that symbiont communities have changed following the introduction int o a non native territory. Although if Xylosandrus and Ambrosiella are tightly co evolved, it is also more likely that symbiont host switches will occur with closely related beetles and fungi. Reports of host switching in insect fungus symbioses are more co mmon in closely related species ( Mueller and Gerardo 2002, Nobre et al. 2011 ). Indeed, C. mutilatus is closely related to X. amputatus and both have similar mesonotal mycangia (Cognato et al. 2011, Dole and Cognato 2010). Another explanation for the appare nt symbiont sharing is that the loci used in identification of Ambrosiella spp. are unable to resolve cryptic species level identities. Other clades of hyperdiverse fungi, such as many Fusarium spp., require the use of six or more loci to differentiate spe cies ( et al. 2008). Further studies need to incorporate more genetic loci in species descriptions and phylogenetic analyses. Ambrosiella is, as the vast majority of ambrosia beetles have never ha d their fungal communities characterized. The lack in studies investigating beetle communities also makes it more difficult to establish how often fungi are traded or shared among different beetle species. Two other symbionts of beetles reported here, R. s ubalba and R. subfusca associated with X. andrewesi and E. validus respectively, were also originally reported to be a symbiont of another beetle, Xyleborus glabratus (Harrington et al. 2010). Many additional Raffaelea spp. have been recovered from diverse fungal communities within the mycangium of X . glabratus . Due to limited geographic sampling and insufficient
36 these relationships uphold across the distribution of the bee tle, and if exotic beetles are changing native beetle symbiont communities. Although results from the present study are limited in geographic scope, they still provide contribute to a broader understanding of patterns in symbiont communities across Xylebo rini ambrosia beetles. Clearer patters only emerge when combining other culture based symbiont reports from the literature. A summary of these reports is provided in Table 2 2, and visualized on a cladogram in Figure 2 5. Only recent studies incorporating molecular markers in fungal identification are included in Table 2 2. The se combined reports of symbiont surveys suggest that the number and identity of symbiotic fungi associated with the beetles varies substantially, and appears to relate to beetle cla de. The fidelity and diversity of beetle fungus relationships may be influenced by mycangium type, which is specific to each beetle clade. Mandibular mycangia, which often host diverse and fluid communities of fungi, may be more permissive to the addition of new symbionts because any fungus traveling through the beetle mouth (either through wood boring or consumption) has a chance of entering the mycangium. Mesonotal mycangia, which are well protected underneath the pronotum, may be less prone to accessory fungal contamination. The diverse ambrosia fungi may also be differently adapted to surviving in different mycangia. Ambrosiella species, which are only consistently found in mesonotal mycangia, may be more co evolved and rely on specific conditions or nut rients only found in their corresponding mycangium. Raffaelea species, which are also found in a variety of mycangium types, may be less co evolved with any single beetle clade and
37 possess traits that allow them to be easily disseminated and acquired by ne w ambrosia beetle species. However, inferences of co evolutionary relationships are dependent on comprehensive taxon sampling of symbionts and dating of divergence times which are still unavailable for ambrosia beetles and fungi. Future studies need to ut ilize both culture and culture independent sampling of symbiont communities to correct for culture bias, allow for higher throughput analyses, and more precisely characterized communities. Experimental evidence also needs to establish roles of symbionts an d how the beetles and fungi interact in a natural landscape to determine what selective pressures are at play in the symbiosis. The results in the present study can be used in future research by directing taxon sampling efforts, and by establishing the cur rent symbionts of exotic ambrosia beetles for future investigation of temporal and geographic variation in symbiont communities.
38 Table 2 1. Prevalence and abundance of fungi isolated from exotic Xyleborini Beetle species Fungal isolate Prevalence on beetl e (%) Mean CFU recovered a Stand. Dev. Euwallacea interjectus Fusarium sp. 100% 2,622.2 2,095.38 Euwallacea validus Fusarium sp. 100% 373.2 312.88 Raffaelea subfusca 100% 278.8 283.47 Xylosandrus amputatus Ambrosiella beaveri 100% 1,088 1,495.7 X yleborinus andrewesi Raffaelea subalba 86% 1,513 2,922.9 a = recovered from location beetle known to transport fungi Table 2 2 . Combined reports of Xyleborini fungal symbionts in the literature and present study Mycangium type Beetle Core fungal assoc iates Cumulative # of associates Reference Mandibular Xyleborus spp. Raffaelea spp. (some times Fusarium sp., others) >6 Harrington et al. 2010, Kasson et al. 2013, Carrillo et al. 2013, Ploetz et al. 2011, Beidermann et al. 2009 Mandibular Euwallacea s pp. Fusarium spp. (some times Raffaelea sp., others) >2 Kasson et al. 2013, Present study Metanotal /abdomen Xyleborinus spp. Raffaelea spp. 1 2 Biedermann at al. 2013, Present study Mesonotal Xylosandrus spp. Ambrosiella spp. 1 Harrington & Fraedrich 20 10, Six et al. 2009, Present study
39 Figure 2 1 . Maximum likelihood based identification of Xylosandrus amputatus mycangial isolate Ambrosiella beaveri with M icroascus cirrosus used as an outgroup . Ingroup sequences are from species of Ceratocystis and Ambrosiella (Microascales) Relationsh tubulin sequence data. Numbers next to nodes are maximum likelihood bootstrap values based on 1,000 bootstrap replicates .
40 F igure 2 2 . Maximum likelihood based identification of Xylosandrus amputatus mycan gial isolate Ambrosiella beaveri with Raffaelea lauricola used as an outgroup . Ingroup sequences are from species of Ceratocystis and Ambrosiella (Microascales) Relationsh ips were inferred from LSU rDNA sequence data. Numbers next to nodes are maximum like lihood bootstrap values based on 1,000 bootstrap replicates .
41 Figure 2 3 . Maximum likelihood based identification of the Xyleborinus andrewesi mycangial isolate Raffaelea subalba with Ambrosiella xylebori used as an outgroup . Ingroup se quences are from species of Raffaelea ( Ophiostomatales ) . Relationsh ips were inferred from LSU rDNA sequence data. Numbers next to nodes are maximum likelihood bootstrap values based on 1,000 bootstrap replicates .
42 Figure 2 4 . Maximum l ikelihood based identification of the Xyleborinus andrewesi mycangial isolate Raffaelea subalba with Ambrosiella xylebori used as an outgroup . Ingroup sequences are from species of Raffaelea ( Ophiostomatales ) . Relationsh tubulin sequence data. Numbers next to nodes are maximum likelihood bootstrap values based on 1,000 bootstrap replicates .
43 Figure 2 5 . Cladogram of main Xyleborini clades corresponding to myangium type and patte rns in symbiont communnities inferred from literature and the present study.
44 CHAPTER 3 PREDICTING FUTURE INVADERS; ARE UNKNOWN PATHOGENS HIDING IN ASIA ? Introduction Forest ecosystems across the world are rapidly undergoing changes in form and functi on as a result of non indigenous (or non native, exotic) species. The arrival of exotic insects and fungi in many cases has initiated a shift in forest compositions and extirpation or extinctions of tree species or their associated communities of organisms (Lovett et al. 2006 , Gand h i and Herms 2010, Brokerhoff et al. 2006). The near removal of American chestnut ( Castanea dentata ) in North America due to Chestnut blight, caused by the fungus Cryphonectria parasitica from Asia, has been accompanied by change s in forest composition, increased tree diversity, disruptions in ecosystem nutrient cycling (Loo 2008) and the loss of American chestnut associated insect species ( Lynne Rieske Kinney , pers. comm. 2014). Similarly, exotic insects such as the exotic emeral d ash borer, asian longhorned beetle, and hemlock wooly adelgid have begun eliminating hardwood and conifer species from north and eastern North America, all likely to bring ecosystem damage that has not yet been quantified . Except for habitat destruction, exotic insects and fungi form the largest immediate threat to biodiversity on earth (Simberloff et al. 2005). Unintentional introductions of insects and fungi have been increasingly frequent following the course of international trade and travel (Wingfiel d et al. 2010). New arrivals of exotic pests are unlikely to decrease since trade and travel are expected to increase, resources limit more stringent trade regulations, and policy compliance is difficult to control. Slowing the rate of introduction is diff icult due to cryptic and pervasive qualities of insects and fungi, and the ability of many species to reproduce asexually. Forest
45 insects and pathogens are most commonly carried to new regions on nursery stock, wood packing materials, produce, and seed (Ha ack 2001). Wood boring insects are especially difficult to control due to their protection from external conditions, such as pesticide treatments, by traveling inside wood. Wood boring bark and ambrosia beetles (Coleoptera: Scolytinae) are among the most c ommonly intercepted exotic forest pests (Haack 2006, Aukema et al. 2010). Although most of these introductions are harmless, a few exotic bark and ambrosia beetles or their associated fungi have been disproportionately detrimental forest pests. Alliances b etween bark and ambrosia beetles (Curculionidae: Scolytinae, Platypodinae) and their associated fungi (members of Ophiostomatales, Microascales, and Hypocreales) are currently driving tree mortality in ecologically and economically important tree species a cross the world. In some cases, trees have undergone massive selection events and regional extirpations as a result of the introduced fungi and beetles (Kendra et al. 2013, Ploetz el al. 2013). Until recently, plant pathogenic fungi identified as associate s of bark beetles have been found to be antagonistic to the survival of the beetle (Six and Wingfield 2011). New forest diseases are increasingly caused by non native fungi that appear nutritionally beneficial to the ambrosia beetles. These disease causing fungal mutualists have only been shown to act as pathogens in non native environments. For example, fungi associated with Xyleborus glabratus (the redbay ambrosia beetle), Pityophthorus juglandis , and Platypus quercivor us are all thought to be non native in the region where they cause harm (Ploetz et al. 2013). Beetles may also display novel characteristics in non native regions, such as attacking live trees rather than dead ones (Hulcr & Dunn 2011). The lack of preliminary data indicating how
46 a species wi ll behave in a non native region makes it almost impossible for government agencies to respond in time to prevent establishment of a pest species. Wait and see Approach A number of government programs are designed to reduce and prevent damages caused by invasive alien species. The Early Detection and Rapid Response program (EDRR, U.S. Forest Service) and Cooperative Agricultural Pest Survey (CAPS, Florida Department of Agriculture and Consumer Services) continually monitor for new and existing invasiv e species, most heavily in ports of entry where exotic organisms are most likely to become introduced (Rabaglia et al. 2008). These programs rely on previous information on the potential for species to become invasive, such as those generated by the USDA A PHIS Offshore Pest Information System (OPIS) or through ecological niche modeling studies. These programs have been successful at preventing ecological and economic destruction from invasive pests, but have been unable to prevent new invasive species intro ductions when too little was known about the organism before its arrival. The USDA OPIS is often unable to predict which exotic beetles and fungi will be destructive because they rely upon existing information on the organisms in their native territory, wh ich is usually either unavailable or not relevant for beetles/fungi which act differently in non native regions. It is not fiscally feasible to prevent every beetle introduction because bark and ambrosia beetle introductions are so common and because most of these introductions appear to be harmless. The beetles and fungi that do cause harm to trees are only discovered to cause disease and number of damaging introduced species, including the redbay ambrosia beetle (RAB). The RAB was detected by the EDRR program more than a year before it was
47 associated with mass mortality of redbays (Fraedrich et al. 2008). The period of time in between introduction and disease occurrence provide s a newly introduced species to establish a population and disperse to new areas effectively making it impossible for eradication. This is especially true for some groups of bark and ambrosia beetles, which can establish a population with a single individu al. Thus, the only opportunity to prevent the establishment of invasive beetles and fungi is through prior knowledge of which species are able to cause significant harm. Preventing the Next Tree Epidemic There have been many approaches used to assess invas ion or pathogen ability in non native species, but such strategies rely on previous knowledge of exotic species. Some studies have focused on generating new data for predictions where prior information was lacking on a potential new pest species. One examp le is the use of their native range and monitored for novel interactions between the host and pests/pathogens (Britton et al. 2010). These transplant studies can pro vide valuable new information about the ability for non native species to cause damage to native plants but require extensive long term sampling and are limited in scope. For example, diseases can be difficult to diagnose and characterize when a whole slew of new organisms are interacting with the non native host, especially when novel abiotic variables such as climate may cause additional stress to the sentinel species. Host pathogen interactions may be further shadowed by the presence of predators in the non native habitat, or absence of native predators. A more systematic approach is necessary to test direct effects of pests on their hosts as a counterpart to these sentinel studies.
48 A new approach, proposed in this study, is to evaluate interactions bet ween native hosts and exotic pests/pathogens in a controlled, quarantined environment before the exotic species is introduced. These pre invasion diagnostic studies may provide exclusive information on the ability for a single exotic species to cause harm to a native species, which is exactly what regulatory agencies need to make decisions for eradication and prevention of newly arriving exotic species. The present study was established as a proof of concept approach for evaluating the potential of fungi as sociated with bark and ambrosia beetles in Asia to act as pathogens to American trees. Three beetles ( Xyleborus pinicola , Tomicus minor , and Ips chinensis ) were selected as potentially invasive based on their occurrence in climates and habitats similar to those in the southeastern United States, and their specificity to pines, which are the most ecologically and economically important tree species in the Southeast (Beeson 1930). Xyleborus pinicola was of particular interest due its ability to establish a po pulation with a single individual, and its unusual host specificity when compared to close beetle relatives. All three beetle species were also chosen because of their close associations to fungi, indicating a high likelihood that they have specific fungal associates that may be transported with the beetle during an introduction to a new region. Specifically, this study was initiated to test the following questions which pre formulated hypotheses could not be made: 1. Is evaluating fungi associated with non n ative bark and ambrosia beetles a feasible approach for assessing pathogen potential before their introduction into a non native region? 2. Are Xyleborus pinicola , Tomicus minor , and Ips chinensis carrying fungi that are pathogenic to trees that are native to the southeastern United States ?
49 3. Are there life history traits of beetle vectors that allow prediction of whether the beetles are carrying fungal tree pathogens? Methods Study Sites and Beetle Collection Fungi used in pathogenicity tests were isolated fro m beetles collected in China and Thailand during May July of 2013. Tomicus minor was collected from several dead Pinus yunnanensis boles in Kunming, Yunnan, China ( 25.068895, 102.762013 ). Ips chinensis was collected from a dying P. armand i i stand in Chuxio ng, Yunnan, China. Xyleborus pinicola and I. chinensis were collected from the bole of a dying P. kes i ya in Hot, Chiang Mai, Thailand (18.144611, 98.319944). Adult beetles were identified using genera (1986), Kirkendall Tomicus (2008 ), and Yin (1984). Voucher specimens of Tomicus spp . were also confirmed by Massimo Faccoli (personal comm. 2013) who originally aided in delimited Tomicus spp. in Yunnan, China (Kirkendall 2008). S pecimens of I. chinensis were confirmed by Anthony Cognato (personal comm. 2013) who is currently working on the systematics of this group . Beetles were stored at 10 15Â° C for up to 48 hours before fungal isolation. Fungal Isolation Fungi were isolated from beetle galleries, and adult, pupal, and larval li fe stages depending on availability. Beetle galleries were sampled by surface disinfesting wood with ethanol and scraping of gallery walls into phosphate buffer saline (PBS) prior to serial dilution. Beetle dissections took place either in a laboratory bio safety hood (Chinese specimens) or inside an ethanol sterilized plastic bin with holes cut in one side to function as a field isolation chamber (Thai specimens). All life stages of beetles were
50 surface washed in a 1 mL sterile solution of 1% Tween 80 (Sigm a Chemical Co, St. Louis, MO, USA) and PBS, which was then was serially diluted prior to plating. Larvae and pupae of all species were individually macerated in PBS prior to serial dilution. Adult T. minor and I. chinensis specimens were sectioned into thr ee parts prior to maceration and dilution: the head, thorax, and abdomen. H ead s of adult X. pinicola foundress females aseptically removed prior to maceration and dilution. Only heads were included for this species because beetles in this genus contain myc angia within the mandibles. Serial dilutions of 1/10, 1/100, and 1/1000 times were made from each sample (location of beetle body). Dilutions were plated on Potato Dextrose Agar amended with 1.4% additional agar and 2% streptomycin . Plates were stored in a n incubator in the dark at 25Â° C for up to two weeks. Morphotypes were designated based on macromorphology for all fungal colon y forming units (CFUs) found in more than one sample. Plates were monitore d every 2 3 days during the two week incubation period and photographed to ensure consistent assignment of morphotypes. Morphotype designations were confirmed by retrospective comparisons of pure cultures and by sequencing portions of the nuclear riboso mal DNA (rDNA) and four protein encoding genes. Molecular Identification and Phylogenetic Analysis One to two week old pure cultures were used for DNA extraction. 10 20 Âµl of mycelium was added to 20 uL of Sigma Aldrich Extraction Solution (Extract N Amp, St. Louis, MO) in 0.25 mL PCR tubes, which were then incu bated in a thermocycler (Eppendorf Mastercycler) at 96Â° C for 10 minutes. After incubation, 20 ÂµL of 3% BSA (Fermentas) was added to each tube, vortexed for 5 sec and then centrifuged at 2000
51 rpms for 30 seconds. The upper half of this solution was used as genomic DNA template for PCR. Morphotype designations were evaluated using both RAPD PCR and Sanger sequencing. Each RAPD PCR contained a final volume of 25 ÂµL: 1 ÂµL of template DNA, 2 ÂµL of M13 primer (10 ÂµM), 0.125 Âµl of Taq (TakaraÂ®), 2.5 ÂµL PCR buffe r (15 mM MgCl2), 2 ÂµL dNTP mix (2.5 mM each dNTP), and 20 ÂµL sterile water. Amplification was performed in an Eppendorf Mastercycler Pro following parameters in (Arnau et al. 1994). RAPD PCRs were run on a 1% agarose gel for 90 minutes at 110V. Each well c ontained 2 ÂµL of SyBr Green dye and either 9 ÂµL template or 10 ÂµL ladder. Basic PCR reactions used in sequencing consisted of a final volume of 25 ÂµL: 1 ÂµL of template DNA, 1 ÂµL of forward and reverse primer (10 ÂµM), 0.125 Âµl of Taq (TakaraÂ®), 2.5 ÂµL PCR buffer (15 mM MgCl2), 2 ÂµL dNTP mix (2.5 mM each dNTP), and 20 ÂµL sterile water. PCR and sequencing primers are listed in Table 1 1 . PCR products were purified using Exosap Corp., Cleveland, OH). PCR reaction s were performed in an Eppendorf Mastercycler Pro following published cycling parameters (Kim et al. 2004). DNA sequencing was performed on an ABI PRISM 377XL or 3130XL automated DNA sequencer by the Interdisciplinary Center for Biotechnology Research, Un iversity of Florida, Gainesville. Forward and reverse sequences were assembled into contigs in Geneious (Version 7.0). Partial sequences were obtained from up to three nuclear ribosomal RNA (rDNA) encoding regions and portions of four protein en coding gene s, from up to five isolates of each morphotype.
52 BLAST queries of the NCBI GenBank database were performed with each sequence to identify the fungi that were cultured. Final taxonomic identities were assigned by phylogenetic comparisons to congeneric sequen ces available in Genbank. Maximum likelihoo d phylogenet ic analyses were performed using PhyML (Guindon et al. 2010) with 1,000 bootstrap replicates. Pathogenicity Test The most common and abundant fungi ( Ophiostoma sp., Ophiostoma ips , Raffaelea sp., and Geosmithia sp.) isolated from each beetle species surveyed was used to create spore suspensions for inoculation into pine seedlings. Spore suspensions were made from sterile water and 10 14 day old fungal cultures plated on Potato Dextrose Agar ( Difco). Spore concentrations reflected the highest total CFU count isolated from a beetle (Table 3 1). The concentration of spore suspensions were calculated using a hemocytometer. Three pine genotypes were tested for pathogenicity, including two Pinus ta eda families, and one P. ellio t tii family. Pine families were provided by Weyerha e user. Pines were stored in a quarantined greenhouse facility at the Division of Plant Industry (DPI), Department of Agriculture and Consumer Services in Gainesville, Florida. The trees were maintained under natural light conditions, watered as necessary, and kept under a night day temperature regime averaging at 27Â° C. Treatments were arranged in a completely randomized design with eight trees per fungus treatment and pine gen otype combination. Each seedling stem was at least 40 cm from neighboring seedlings A single hole was drilled at a downward angle (approx. 45 degrees) into the xylem of each seedling using a 1.98 mm (5/64 inch) drill bit. Holes were made within the basal 3 0 cm of the stem and were up to 4 cm deep. The diameter of the stem at the
53 inoculation site was an average of 1.4 cm. Spore suspensions were pipetted into the xylem in 50 uL aliquots. Wound sites were wrapped in parafilm immediately following inoculation. Seedlings were monitored weekly for signs of mortality and disease development (including foliar discoloration, wilting, resinosis, and mortality). After 10 weeks, seedlings were destructively sampled. Bark was carefully scrapped away using a knife to allo w for measurement of phloem necrosis or cankers. A razor was used to cut vertical sections of the inner stem to allow for measurement of stain in the xylem (Figure 3 1). Stem sections were stored for up to two days at 10Â° C prior to attempted re isolation of inoculated fungi. Stained and un stained portions of the xylem above and below the inoculation point were surface disinfested and plated on PDA (Difco) incubated at 25Â° C. Differences in disease expression (resinosis, lesion size) was tested using a one tailed t Results Fungal Isolations and Identification Genotyping isolates by RAPD PCR and Sanger sequencing narrowed fungal is olates to five morphotypes that were isolated from at least 75% of re spective beetles sampled (Table 3 1). BLAST queries and phylogenetic analyses identified the five isolates as Ophiostoma sp., O. ips, Raffaelea sp ., and Geosmithia sp. ( Dreaden et al. in review ). Isolates of O. ips from both China and Thailand were assayed in this study based on a 1% diverge nce in B tubulin gene sequences between the two cultures.
54 Pathogenicity Test Across all pine genotypes before destructive sampling, resin production at the inoculation site was the only symptom of disease development th at was significantly different compared to the control for some treatments. Only Ophiostoma ips and O. sp. displayed significantly longer periods of resinosis compared to the control ( Table s 3 2 to 3 4 ) . Destructive sampling after 10 weeks showed that lesi ons in the xylem and phloem of O. ips and O. sp. were significantly longer compared to controls across all pine families, except in loblolly pine family 2, which displayed no difference in xylem lesion length when inoculated with Ophiostoma sp. (Table s 3 5 to 3 10 ). There were no differences observed in pathogenicity between O. ips genotypes from China and Thailand when compared to controls. Re isolation of all Ophiostoma isolates from the xylem of Pinus taeda were successful . Raffaelea sp. and Geosmithia sp. displayed no significant differences in symptoms during the period allowed for disease development (Tables 3 2 to 3 4) . Phloem and xylem lesion lengths in Raffaelea and Geosmithia treatments were not t est (Tables 3 5 to 3 10). No mortality occurred during the experiment. No significant wilting or foliar discoloration was observed during the experiment in any treatment. Except for resin production and small cankers at wound sites, all seedlings appeared healthy and formed call us es at the end of the experiment. Discussion This study validates the feasibility of rapidly assessing pathogen potential in cryptic, symbiotic organisms that are from non native regions and not yet established outside their nativ e range . The approach implemented here demonstrated that two
55 beetle associated Ophiostoma spp. isolated from Ips chinensis and one from Xyleborus pinicola were able to cause disease symptoms in Pinus taeda or P. elliotti , while two other beetle associated fungi from Asia did not cause noticeable symptoms of disease. Results presented here suggest that none of the fungi tested are able to act as deadly vascular wilt pathogens, and thus they are unlikely to cause a significant number of tree deaths in North A merican forests. The pathogenicity of Ophiostoma ips inferred from resin production and xylem lesions in the present study is consistent with previous studies that have shown that O. ips is able to act as a pathogen on American trees, and has already been introduced into North America (Kim et al. 2003, Lim et al. 2006). Ophiostoma ips has also been documented in association with many species of bark beetle species in Europe, Asia, and North America. Greater taxon sampling and experimental evidence is needed to establish how diverse O . ips is across large geographic scales, how it maintains association to beetles, and whether it is transported as a nutritional symbiont or plays some other role. The Ophiostoma sp. was observed to be less pathogenic compared to O . ips based on less significant differences resin production and length of lesions when Ophiostoma sp. was also found to be less prevalent than O. ips on Ips chinensis suggesting it may be less strictly associated or pla y some other role in the symbiosis. Unless the Ophiostoma sp. is able to cause further damage to trees through mass attack of beetles, it is unlikely that the introduction of this fungus species would cause any significant harm to Pinus spp. in the southea stern United States. In cases where invasive bark beetles have caused widespread damage to trees,
56 it has been typically the action of the beetle mass attack or a highly virulent fungus in causing tree death, rather than weakly pathogenic associated fungi ( Six and Wingfield 2011) . Nonetheless, future studies should include treatments with multiple inoculation sites to test the response of trees to mass attacks of beetle in troduced fungi, and may benefit from the assay of more tree host species. The two fungi that did not induce significant symptoms of disease, Raffaelea sp., and Geosmithia sp., are probably harmless to living trees. The vast majority of species within these genera are harmless to trees , and the isolates included in this study are not closely related to disease causing species (Kostovcik et al. in pre p , Dreaden et al. in prep ). One caveat to this finding is that symptoms may be differently expressed in older trees, or take longer than 10 weeks to be expressed. However, all other vascular wilt p athogens capable of killing large numbers of trees are able kill even seedlings and are able to do so in under 12 weeks (Fraedrich et al. 2008, Townsend et al. 1995, Yadeta and Thomma 2013). For this reason , Raffaelea sp. and Geosmithia sp. are still unlik ely to be mass tree killing vascular wilt pathogens. In addition, these fungi were not recovered from stained sapwood ab ove and below inoculation sites. This indicates they may have difficulty growing inside living, healthy xylem whereas vascular wilt path ogens would be expected to readily spread via healthy xylem. The low to absent pathogenicity observed in the present study suggests that none of the fungi found associated with Tomicus minor, Xyleborus pinicola , or Ips chinensis warrants a high threat rati ng. However, we need to document the fungal communities of these same beetles across wider areas in Asia in order to determine whether other potentially dangerous fungi might be present in other parts of the range of
57 these beetles, and how specific the ass ociations seen in this study hold true across geographically disparate locations. Combining ecological understanding from experimental and exploratory research of invasive species will become increasingly important as new pests and pathogens become establi shed around the world. Trees provide profound structuring to native ecosystems and have specific coevolved assembles which become disrupted following the introduction of an invasive pathogen (Thomson 2005). Preventative approaches to management of invasive species are ideal for saving valuable economic and ecological resources such as trees used in forestry . The current reactive approach is too permis sive to pests and pathogens that have not been characterized. The pre invasion diagnostic presented in this study offers government regulatory agencies the opportunity to increase the focus of their prevention and eradication efforts by generating necessary information on those species that are likely to become invasive.
58 Figure 3 1 . Sympto ms of Ophiostoma ips on Pinus taeda seedling stems during disease development (left) and after destructive sampling (lateral bisection, right). Table 3 1. Prevalence and abundance of fungi associated with Asian bark beetles sampled. Beetle species Fungal i solate Prevalence on beetle (%) Prevalence in gallery (%) Spore amount used in inoculation experiment Ips chinensis Ophiostoma sp. 75 75 2,000 Ophiostoma ips 100 86 1,9 00 Tomicus minor Geosmithia sp . 100 72 1,22 0 Xyleborus Ophiostoma ips 60 80 2,50 0 pinicola Raffaelea sp. 100 80 3,5 00 Table 3 2 . Mean number of weeks seedlings displayed resin production in loblolly pine genotype 1 inoculated with Asian fungi. Treatment Mean sd p value a Control 1.5 1.069 Ophiostoma sp. 1.75 2.0529 0.383 Ophio stoma ips 3.12 1.1259 0.005 Ophiostoma ips 2.75 1.983 0.0727 Raffaelea sp. 1.75 1.488 0.353 Geosmithia sp. 1.25 1.1649 0.6692 a tailed t test
59 Table 3 3 . Mean number of weeks seedlings displayed resin production in loblolly pine genotype 2 inoculated with Asian fungi. Treatment Mean sd p value a Control 0.88 0.641 Ophiostoma sp. 2.5 1.6903 0.0158 Ophiostoma ips 4.5 2.0702 3.27E 05 Ophiostoma ips 3.75 1.9226 0.0037 Raffaelea sp. 1.37 0.744 0.0861 Geosmithia sp. 1.75 1. 3887 0.06858 a tailed t test Table 3 4 . Mean number of weeks seedlings displayed resin production in slash pine inoculated with Asian fungi. Treatment Mean sd p value a Control 2.5 2.7255 Ophiostoma sp. 3.5 1.9272 0.2063 O phiostoma ips 5.5 2.3905 0.0743 Ophiostoma ips 5 2.8284 0.0467 Raffaelea sp. 2.5 2.0701 0.5 Geosmithia sp. 4 2.2039 0.1235 a tailed t test Table 3 5 . Mean vertical xylem lesion length in loblolly pine genotype 1 inoculated w ith Asian fungi. Treatment Mean sd p value a group Control 0.83125 0.3788 a Ophiostoma sp. 1.775 0.6041 0.0014 b Ophiostoma ips 3.513 0.6443 2.52E 07 c Ophiostoma ips 3.7875 0.9046 5.09E 06 c Raffaelea sp. 1.371 0.1704 0.0023 ab Geosmithia sp. 1.13 75 0.4983 0.1181 a a tailed t test b Table 3 6 . Mean vertical xylem lesion length in loblolly pine genotype 2 inoculated with Asian fungi. Treatment Mean sd p value a group b Control 0.6571 0. 1718 a Ophiostoma sp. 2.2375 0.7782 0.0002 b Ophiostoma ips 4.075 1.416 2.67E 05 c Ophiostoma ips 4.7 1.2375 1.10E 04 c Raffaelea sp. 1.3313 0.4605 0.0019 a Geosmithia sp. 1.1375 0.3889 0.01004 a a tailed t test b corresp
60 Table 3 7 . Mean vertical xylem lesion length in slash pine inoculated with Asian fungi. Treatment Mean sd p value a group b Control 0.975 0.3196 a Ophiostoma sp. 1.9285 0.4535 0.00039 a Ophiostoma ips 3.95 2.1105 0.00148 b Ophiostoma ips 3.9375 0.8433 0.00255 b Raffaelea sp. 1.2 0.239 0.6744 a Geosmithia sp. 1.1375 0.3159 0.3238 a a tailed t test b Table 3 8 . Mean vertical phloem lesion length in loblolly pin e genotype 1 inoculated with Asian fungi. Treatment Mean sd p value a group b Control 0.4875 0.3613 a Ophiostoma sp. 1.1375 0.30207 0.0008 b Ophiostoma ips 1.9375 0.5926 4.15E 05 c Ophiostoma ips 2.4857 0.7151 5.54E 05 d Raffaelea sp. 0.7714 0.2563 0.0504 ab Geosmithia sp. 0.6625 0.4274 0.1959 ab a tailed t test b Table 3 9 . Mean vertical phloem lesion length in loblolly pine genotype 2 inoculated with Asian fungi. Treatment Mean sd p v alue a group b Control 0.5687 0.3673 a Ophiostoma sp. 1.0428 0.2878 0.007 a Ophiostoma ips 1.6125 0.6556 0.0012 b Ophiostoma ips 2 0.7071 0.0002 b Raffaelea sp. 0.7313 0.0704 0.1281 a Geosmithia sp. 0.575 0.3694 0.4867 A a ne tailed t test b Table 3 10 . Mean vertical phloem lesion length in slash pine inoculated with Asian fungi. Treatment Mean sd p value a group b Control 0.5714 0.3352 a Ophiostoma sp. 0.8625 0.0876 0.0312 ab Ophiost oma ips 1.55 0.4504 2.00E 04 b Ophiostoma ips 1.6429 0.48599 3.00E 04 b Raffaelea sp. 0.7875 0.2531 0.0954 ab Geosmithia sp. 0.625 0.324 0.3795 a a tailed t test b
61 LIST OF REFERENCES Alamou ti, M., S., Tsui, C. K., & Breuil, C. (2009). Multigene phylogeny of filamentous ambrosia fungi associated with ambrosia and bark beetles. Mycological research , 113 (8), 822 835. Arnau, J., Housego, A. P., & Oliver, R. P. (1994). The use of RAPD markers in t he genetic analysis of the plant pathogenic fungus Cladosporium fulvum. Current genetics , 25 (5), 438 444. Atkinson, T. H., Rabaglia, R. J., & Bright, D. E. (1990). Newly detected exotic species of Xyleborus (Coleoptera: Scolytidae) with a revised key to spe cies in eastern North America. The Canadian Entomologist , 122 (01), 93 104. Aukema, J. E., McCullough, D. G., Von Holle, B., Liebhold, A. M., Britton, K., & Frankel, S. J. (2010). Historical accumulation of nonindigenous forest pests in the continental Unit ed States. Bioscience , 60 (11), 886 897. Baker, J. M., & Norris, D. M. (1968). A complex of fungi mutualistically involved in the nutrition of the ambrosia beetle Xyleborus ferrugineus. Journal of Invertebrate Pathology, 11(2), 246 250. Banno, I., Mikata, K., & Kodama, K. (1983). Ascomycetous yeasts isolated from galleries of the ambrosia beetles in Japan. Trans. Mycol. Soc. Jpn , 24 , 441 450. Batra, L. R. (1967). Ambrosia fungi: a taxonomic revision, and nutritional studies of some species. Mycologia, 59, 9 76 1017. Beeson, C. F. C. (1930). The biology of the genus Xyleborus, with more new species. Indian Forest Records , 14 (pt. 10), 209 272. Bhat, S. S., & Sreedharan, K. (1988). Association of Ambrosiella xylebori Brader, with the shot hole borer Xylosandrus compactus Eichhoff, a pest of robusta coffee. Journal of Coffee Research, 18(1), 54 57. Brader, L. (1964). Ã‰tude de la relation entre le scolyte des rameaux du cafÃ©ier Xyleborus compactus Eichh.(X. morstatti Hag), et sa plante hÃ´te. H. Veenman & Zonen NV. Bright, D. E., & Rabaglia, R. J. (1999). Dryoxylon, a new genus for Xyleborus onoharaensis Murayama, recently established in the southeastern United States (Coleoptera: Scolytidae). The Coleopterists' Bulletin , 333 337. Britton, K. O., White, P., Kramer, A ., & Hudler, G. (2010). A new approach to stopping the spread of invasive insects and pathogens: early detection and rapid response via a global network of sentinel plantings. New Zealand Journal of Forestry Science , 40 .
62 Carrillo, D., Duncan, R. E., Ploetz , J. N., Campbell, A. F., Ploetz, R. C., & PeÃ±a, J. E. (2014). Lateral transfer of a phytopathogenic symbiont among native and exotic ambrosia beetles. Plant Pathology, 63(1), 54 62. Cognato, A. I., Hulcr, J., Dole, S. A., & Jordal, B. H. (2011). Phylogeny of haplo diploid, fungus growing ambrosia beetles (Curculionidae: Scolytinae: Xyleborini) inferred from molecular and morphological data. Zoologica Scripta , 40 (2), 174 186. Daehler, C. C., & Dudley, N. I. C. K. (2002). Impact of the black twig borer, an introduced insect pest, on Acacia koa in the Hawaiian Islands. MICRONESICA AGANA , 35 , 35 53. Darriba, D., Taboada, G. L., Doallo, R., & Posada, D. (2012). jModelTest 2: more models, new heuristics and parallel computing. Nature Methods , 9 (8), 772 772. Dole, S. A., & Cognato, A. I. (2010). Phylogenetic revision of Xylosandrus Reitter (Coleoptera: Curculionidae: Scolytinae: Xyleborina). Proceedings of the California Academy of Sciences , 61 (7), 451. Faccoli, M., Frigimelica, G., Mori, N. I. C. O. L. A., Petrucco Toffolo, E., Vettorazzo , M., & Simonato, M. (2009). First record of Ambrosiodmus (Hopkins, 1915) (Coleoptera: Curculionidae, Scolytinae) in Europe. Zootaxa , 2303 , 57 60. Francke Grosmann, H. (1952). Ãœber die Ambrosiazucht der beiden KiefernborkenkÃ¤fer Myelophilus minor Htg. und I ps acuminatus Gyll. Francke Grosmann, H. (1967). Ectosymbiosis in wood inhabiting insects. symbiosis , 2 , 141 205. Gandhi, K. J., & Herms, D. A. (2010). Direct and indirect effects of alien insect herbivores on ecological processes and interactions in forest s of eastern North America. Biological Invasions , 12 (2), 389 405. Gandhi, K. J., Cognato, A. I., Lightle, D. M., Mosley, B. J., Nielsen, D. G., & Herms, D. A. (2010). Species composition, seasonal activity, and semiochemical response of native and exotic b ark and ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) in northeastern Ohio. Journal of economic entomology , 103 (4), 1187 1195. Gebhardt, H., Weiss, M., & Oberwinkler, F. (2005). Dryadomyces amasae: a nutritional fungus associated with ambrosia beetles of the genus Amasa (Coleoptera: Curculionidae, Scolytinae). Mycological research , 109 (6), 687 696. Glass, N. L., & Donaldson, G. C. (1995). Development of primer sets designed for use with the PCR to amplify conserved genes from filamentous ascomy cetes. Applied and Environmental Microbiology , 61 (4), 1323 1330.
63 Guindon, S., Dufayard, J. F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010). New algorithms and methods to estimate maximum likelihood phylogenies: assessing the performance of PhyML 3.0. Systematic biology , 59 (3), 307 321. Guindon, S., & Gascuel, O. (2003). A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Systematic biology , 52 (5), 696 704. Haack, R. A. (2001). Intercepted Scolytidae (C oleoptera) at US ports of entry: 1985 2000. Integrated Pest Management Reviews , 6 (3 4), 253 282. Hara, A. H., & Beardsley Jr, J. W. (1976). The biology of the black twig borer, Xylosandrus compactus (Eichhoff), in Hawaii. Proceedings of the Hawaiian Entomo logical Society , 23 (1), 55 70. Harrington, T. C., Aghayeva, D. N., & Fraedrich, S. W. (2010). New combinations in Raffaelea, Ambrosiella, and Hyalorhinocladiella, and four new species from the redbay ambrosia beetle, Xyleborus glabratus. Mycotaxon , 111 (1), 337 361. Harrington, T. C., M. R. Kazmi, A. M. Al Sadi, and S. I. Ismail. 2014. Intraspecific and intragenomic variability of ITS rDNA sequences reveals taxonomic problems in Ceratocystis fimbriata sensu stricto. Mycologia 106:224 242. doi:10.3852/13 189 Hill, D. S. (1987). Agricultural insect pests of temperate regions and their control . CUP Archive. Hofstetter, V., Miadlikowska, J., Kauff, F., & Lutzoni, F. (2007). Phylogenetic comparison of protein coding versus ribosomal RNA coding sequence data: a cas e study of the Lecanoromycetes (Ascomycota). Molecular phylogenetics and evolution , 44 (1), 412 426. Hulcr, J., & Cognato, A. I. (2010). Repeated evolution of crop theft in fungus farming ambrosia beetles. Evolution , 64 (11), 3205 3212. Hulcr, J., & Dunn, R. R. (2011). The sudden emergence of pathogenicity in insect fungus symbioses threatens naive forest ecosystems. Proceedings of the Royal Society B: Biological Sciences , 278 (1720) , 2866 2873. Kaneko, T., Tamaki, Y., & Takagi, K. (1965). Preliminary report on the biology of some Scolytid beetles, the tea root borer, Xyleborus germanus Blanford, attacking tea roots, and the tea stem borer, Xyleborus compactus Eichhoff, attacking tea twigs. Japanese Journal of Applied Entomology and Zoology , 9 (1), 23 28.
64 Geiser, D. M. (2013). An inordinate fondness for Fusarium: Phylogenetic diversity of fusa ria cultivated by ambrosia beetles in the genus Euwallacea on avocado and other plant hosts. Fungal Genetics and Biology , 56 , 147 157. Kendra, P. E., Montgomery, W. S., Niogret, J., & Epsky, N. D. (2013). An uncertain future for American Lauraceae: A leth al threat from redbay ambrosia beetle and laurel wilt disease (A review). American Journal of Plant Sciences , 4 , 727 . Kim, J. J., Kim, S. H., Lee, S., & Breuil, C. (2003). Distinguishing Ophiostoma ips and Ophiostoma montium, two bark beetle associated sapstain fungi. FEMS Microbiology Letters , 222(2), 187 192. Kim, J. J., Lim, Y. W., Wingfield, M. J., Breuil, C., & Kim, G. H. (2004). Leptographium bistatum sp. nov., a new species with a Sporothrix synanamorph from Pinus radiata in Korea. Myc ological research , 108 (6), 699 706. Kinuura, H. (1995). Symbiotic fungi associated with ambrosia beetles. Japan Agricultural Research Quarterly , 29 , 57 57. Kirkendall, L. R. , Faccoli, M., Ye, H. (2008). Description of the Yunnan shoot borer, Tomicus yunnan ensis Kirkendall & Faccoli sp. n.(Curculionidae, Scolytinae), an unusually aggressive pine shoot beetle from southern China, with a key to the species of Tomicus. Zootaxa , 1819 , 25 39. Scolytodes unipunctatus( Coleoptera: Curculionidae, Scolytinae). Mycological research , 113 (1), 44 60. KÃ¼hnholz, S., Borden, J. H., & Uzunovic, A. (2001). Secondary ambrosia beetles in apparently healthy trees: adaptations, potential causes and suggested research. Integrated Pest Management Reviews , 6 (3 4), 209 219. Kuo, H. C. (2010). Plant fungus beetle interactions: Case studies in Hawaiian endemic Xyleborus species and the black twig borer. Multivariate analysis of ecological data using CANOCO . Cambridge university press. Lim, Y. W., Alamouti, S. M., Kim, J. J., Lee, S., & Breuil, C. (2004). Multigene phylogenies of Ophiostoma clavigerum and closely related species from bark beetle attacked Pinus in North America. FEMS microbiology letters , 237 (1), 89 96. Liu, Y. J., & Hall, B. D. (2004). Body plan evolution of ascomycetes, as inferred from an RNA polymerase II phylogeny. Proceedings of the N ational Academy of Sciences of the United States of America , 101 (13), 4507 4512.
65 Masuya, H. (2007). Note on the dieback of Cornus florida caused by Xylosandrus compactus. Bulletin of the Forestry and Forest Products Research Institute , 6 . McClanahan HS. ( 1 951 ) . Grove Inspection Department. Florida State Plant Board, Biennial Report 18: 41 42. McPherson, B. A., Wood, D. L., Erbilgin, N., & Bonello, P. (2010, April). Ambrosia Beetles and Their Associated Fungi Appear to Accelerate Mortality in Phytophthora r amorum Infected Coast Live Oaks. In Sudden Oak Death Fourth Science Symposium (p. 347). McPherson, B. A., Erbilgin, N., Bonello, P., & Wood, D. L. (2013). Fungal species assemblages associated with Phytophthora ramorum infected coast live oaks following b ark and ambrosia beetle colonization in northern California. Forest Ecology and Management , 291 , 30 42. Morales Ramos, J. A., Rojas, M. G., Sittertz Bhatkar, H., & SaldaÃ±a, G. (2000). Symbiotic relationship between Hypothenemus hampei (Coleoptera: Scolytid ae) and Fusarium solani (Moniliales: Tuberculariaceae). Annals of the Entomological Society of America , 93 (3), 541 547. Mueller, U. G., Gerardo, N. M., Aanen, D. K., Six, D. L., & Schultz, T. R. (2005). The evolution of agriculture in insects. Annual Revie w of Ecology, Evolution, and Systematics , 563 595. Muthappa, B. N., & Venkatasubbaiah, P. (1981). Association of Ambrosiella macrospora with Xylosandrus compactus, the shot hole borer of robusta coffee in India. Journal of coffee research , 11 (2). Ngoan, N. D., Wilkinson, R. C., Short, D. E., Moses, C. S., & Mangold, J. R. (1976). Biology of an introduced ambrosia beetle, Xylosandrus compactus, in Florida. Annals of the Entomological Society of America , 69 (5), 872 876. Nishida, G. M., & Evenhuis, N. L. (20 00). Arthropod pests of conservation significance in the Pacific: A preliminary assessment of selected groups. Invasive species in the Pacific: A technical review and draft regional strategy , 115. O'Donnell, K. (1992). Ribosomal DNA internal transcribed spa cers are highly divergent in the phytopathogenic ascomycete Fusarium sambucinum (Gibberella pulicaris). Current genetics , 22 (3), 213 220. O'Donnell, K., & Cigelnik, E. (1997). Two Divergent Intragenomic rDNA ITS2 Types within a Monophyletic Lineage of the Fungus Fusarium Are Nonorthologous. Molecular phylogenetics and evolution , 7 (1), 103 116. origins of the fungus causing Panama disease of banana: concordant evidenc e
66 from nuclear and mitochondrial gene genealogies. Proceedings of the National Academy of Sciences , 95 (5), 2044 2049. O'Donnell, K. (2000). Molecular phylogeny of the Nectria haematococca Fusarium solani species complex. Mycologia , 919 938. O'Donnell, K., S utton, D. A., Rinaldi, M. G., Sarver, B. A., Balajee, S. A., Schroers, H. J., R. C. Summerbell, Robert, V. A.,Crous, P.W., Zhang , N., & Geiser, D. M. (2010). Internet accessible DNA sequence database for identifyi ng fusaria from human and animal infections. Journal of clinical microbiology , 48 (10), 3708 3718. O'Donnell, K., Sutton, D. A., Fothergill, A., McCarthy, D., Rin aldi, M. G., Brandt, M. E., Zhang, H., & Geiser, D. M. (2008). Molecular phylogenetic diversity , multilocus haplotype nomenclature, and in vitro antifungal resistance within the Fusarium solani species complex. Journal of Clinical Microbiology , 46 (8), 2477 2490. Oliveira, C. M., Flechtmann, C. A., & Frizzas, M. R. (2008). First record of Xylosandrus compactus (Eichhoff)(Coleoptera: Curculionidae: Scolytinae) on soursop, Annona muricata L.(Annonaceae) in Brazil, with a list of host plants.The Coleopterists Bulletin, 62(1), 45 48. Pennacchio, F., Santini, L., & Francardi, V. (2012). Bioecological notes on Xylosandrus compactus (Eichhoff)(Coleoptera Curculionidae Scolytinae), a species recently recorded into Italy. Redia, 95, 67 77. Rabaglia, R., Duerr, D., Acciavatti, R., & Ragenovich, I. (2008). Early detection and rapid response for non native bark a nd ambrosia beetles. US Department of Agriculture Forest Service, Forest Health Protection . Reeb, V., Lutzoni, F., & Roux, C. (2004). Contribution of RPB 2 to multilocus phylogenetic studies of the euascomycetes (Pezizomycotina, Fungi) with special emphasi s on the lichen forming Acarosporaceae and evolution of polyspory. Molecular phylogenetics and evolution , 32 (3), 1036 1060. Simberloff, D., Parker, I. M., & Windle, P. N. (2005). Introduced species policy, management, and future research needs. Frontiers i n Ecology and the Environment , 3 (1), 12 20. Six, D. L., & Wingfield, M. J. (2011). The role of phytopathogenicity in bark beetle fungus symbioses: a challenge to the classic paradigm. Annual review of entomology , 56 , 255 272. Thompson, J. N. (2005). The ge ographic mosaic of coevolution . University of Chicago Press. Townsend, A. M., Bentz, S. E., & Johnson, G. R. (1995). Variation in response of selected American elm clones to Ophiostoma ulmi. Journal of environmental horticulture , 13 , 126 126.
67 Vilgalys, R., & Hester, M. (1990). Rapid genetic identification and mapping of enzymatically amplified ribosomal DNA from several Cryptococcus species. Journal of Bacteriology , 172 (8), 4238 4246. Von Arx, J. A., & Hennebert, G. L. (1965). Deux champignons ambrosia.Mycop athologia, 25(3), 309 315. White, T. J., Bruns, T., Lee, S. J. W. T., & Taylor, J. W. (1990). Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR protocols: a guide to methods and applications , 18 , 315 322. Wood, S. L. (1982). The bark and ambrosia beetles of North and Central America (Coleoptera: Scolytidae), a taxonomic monograph. The bark and ambrosia beetles of North and Central America (Coleoptera: Scolytidae), a taxonomic monograph. Yadeta, K. A., & Thomma, B. P. ( 2013). The xylem as battleground for plant hosts and vascular wilt pathogens. Frontiers in plant science , 4 . Zhang, N., O'Donnell, K., Sutton, D. A., Nalim, F. A., Summerbell, R. C., Padhye, A. A., & Geiser, D. M. (2006). Members of the Fusarium solani spe cies complex that cause infections in both humans and plants are common in the environment. Journal of Clinical Microbiology, 44(6), 2186 2190. Von Arx, J. A., & Hennebert, G. L. (19 65). Deux champignons ambrosia Mycopathologia, 25(3), 309 315.
68 BIOGRAP HICAL SKETCH Craig grew up exploring the forests of southern Michigan, where his passion for understanding nature around him was his focus since he can remember. After deeply exploring the world of birds and ornithology as a teenager, he soon learned that insects and fungi abounded with more interesting mysteries and his passions shifted to the field of entomology as a student at Michigan State University (MSU). Before receiving his Bachelor of Science from MSU, his research focused on interactions between mosquitos and microbes under the guidance of Drs. Michael Kaufman and Edward Walker. His growth and experience as a scientist during his undergraduate career gave him new interests in symbioses, leading him to investigate the relationships between ambrosia beetles, fungi, and trees at the University of Florida, where he received his Master of Science working with Jiri Hulcr.
Willclimatechangepromotefutureinvasions? CELINEBELLARD*,WILFRIEDTHUILLER Â† ,BORISLEROY Â‡ Â§ ,PIEROGENOVESI Â¶ ,MICHEL BAKKENES k andFRANCKCOURCHAMP* * Ecologie,Syste Â´ matique&Evolution,UMRCNRS8079,Univ.Paris-Sud,OrsayCedexFR-91405,France, Â† Laboratoire dÂ’EcologieAlpine,UMRCNRS5553Universite Â´ JosephFourier,Grenoble1BP53,GrenobleCedex9FR-38041,France, Â‡ URUEM420Biodiversite Â´ etGestiondesTerritoires,Universite Â´ deRennes1,CampusdeBeaulieu,RennesCedex35042,France, Â§ ServiceduPatrimoineNaturel,MNHN,Paris,France, Â¶ InstituteforEnvironmentalProtectionandResearch,Rome,Italy, k NetherlandsEnvironmentalAssessmentAgency(PBL),POBox303,Bilthoven3720,TheNetherlands Abstract Biologicalinvasionisincreasinglyrecognizedasoneofthegreatestthreatstobiodiversity.Usingensembleforecasts fromspeciesdistributionmodelstoprojectfuturesuitableareasofthe 100oftheworldÂ’sworstinvasivespecies deÃžned bytheInternationalUnionfortheConservationofNature,weshowthatbothclimateandlandusechangeswill likelycausedrasticspeciesrangeshifts.Lookingatpotentialspatialaggregationofinvasivespecies,weidentifythree futurehotspotsofinvasioninEurope,northeasternNorthAmerica,andOceania.Wealsoemphasizethatsome regionscouldloseasigniÃžcantnumberofinvasivealienspecies,creatingopportunitiesforecosystemrestoration. Fromthelistof100,scenariosofpotentialrangedistributionsshowaconsistentshrinkingforinvasiveamphibians andbirds,whileforaquaticandterrestrialinvertebratesdistributionsareprojectedtosubstantiallyincreaseinmost cases.Giventheharmfulimpactstheseinvasivespeciescurrentlyhaveonecosystems,thesespecieswilllikely dramaticallyinÃŸuencethefutureofbiodiversity. Keywords: Climatechange,invasivespecies,landusechange,speciesdistributionmodels Received24May2013andaccepted17July2013 Introduction Climatechanges,includingextremeclimaticevents (i.e.,ÃŸood,Ãžres),canenhanceinvasionprocesses,from initialintroductionthroughestablishmentandspread (Walther etal. ,2009;Diez etal. ,2012),andconsequentlyhaveaprofoundinÃŸuenceontheenvironment. Inaddition,humanactivitiessuchastranscontinental transportation,landdegradationandagricultural systems,leadtothespreadofmanynon-indigenous species(Foley etal. ,2005).Thus,theconcurrenteffects ofclimateandlandusechangescanfurtherincrease thealreadydramaticratesofbiologicalinvasions.For example,inEuropethenumberofinvasivealien speciesincreasedby76%inthelast30years(Butchart etal .,2010).Invasivealienspeciesarelikelycausingan arrayofecological,economicandhealthimpactsfor invadedcountries(Simberloff etal., 2012),thatmay becomevisibleonlylongafterintroduction(Essl etal. , 2011).However,ourlimitedknowledgeoftheimpacts ofclimateandlandusechangesonbiologicalinvasions hindersourabilitytomeasure,predict,andmitigate thegrowingeffectsofthesetwofactorsoninvasive alienspecies.Therefore,thequestionofhowtheinterplaybetweenclimateandlandusechangewillinÃŸuencetheglobalprocessofinvasionsisthusbecoming ofprimerelevancefornaturalresourcemanagement. Moreover,anticipatingfuturedistributionsofinvasive alienspeciesisessentialtofacilitatepre-emptiveand effectivemanagementactionssuchaspreventionof introductionsandopportunitiesforeradication.Risk mapssummarizinglandsuitabilityforinvaderscanbe usefultoolsforanticipatingspecies'invasionsandcontrollingtheirspread(Jim enez-Valverde etal. ,2011). IdentiÃžcationofareaswherepoliciescouldbeneÃžtfrom synergiesbetweenclimate,landusechangeandinvasivespeciesmanagementisalsoofprimerelevance. Attemptstopredictfutureecologicallysuitableareas fortheestablishmentofinvasivealienspecieshave beenmadeonsinglespecies(O'Donnell etal., 2012; Ficetola etal. ,2007;Larson&Olden,2012).Whilemany authorshavewarnedaboutthepotentialsynergistic feedbacksbetweenclimateandlandusechangeson speciesdistributions(Brook etal. ,2008;Hellmann etal. , 2008;Walther etal. ,2009),fewstudieshaveexamined theseinteractionsexplicitly(Murray etal., 2012;Jetz etal. ,2007;Butchart etal. ,2012;Leroy etal. ,2013)and nonehavedonesospeciÃžcallyforanyinvasivealien species.Toaddressthisgap,wereporthereacomprehensiveevaluationofthedualeffectsofclimateand landusechangesonthe 100oftheworldÂ’sworstinvasive Correspondence:CelineBellard,tel:+33(0)169155685, fax+33(0)169155696,e-mail:firstname.lastname@example.org Â© 2013JohnWiley&SonsLtd 3740 GlobalChangeBiology(2013) 19 ,3740Ã3748,doi:10.1111/gcb.12344
species fromtheInternationalUnionfortheConservationofNaturelistoftheInvasiveSpeciesSpecialist Group.Thislistregroupsspecieswithsomeofthelargestimpactsonbiodiversityand/orhumanactivityand representsarangeofecologicalstrategiesover10differenttaxonomicgroups. Inthisstudy,weusedensembleforecastprojections extractedfrommultiplespeciesdistributionmodels (SDMs),severalglobalclimatemodels,andlandcover changescenariostopredictfuturesuitabilityforeachof the100invasivealienspecies.Second,usingthese ensembleprojections,wemappedthepotentiallevelof invasionatdifferenttime-slices(current,2050and 2100).Third,usingprojectedspeciesrangechangesfor thedifferenttaxonomicgroupsofthe100invasivealien species,weassessedthefuturevulnerabilityofvarious biometypestotheseinvasivealienspecies.MaterialsandmethodsDataClimatedata.Tocharacterizepresent-dayclimate,weused climaticdata(averagedfrom1950 Â– 2000)fromtheWorldclim database(Hijmans etal. ,2005)ata0.5 Â° resolution.Weselected sixclimaticvariables:(i)meandiurnalrangel,(ii)maximum temperatureofwarmestmonth,(iii)minimumtemperatureof coldestmonth,(iv)annualprecipitation,(v)precipitationof wettestmonth,and(vi)precipitationofdriestmonth(TableS1 forreferencesdetails).Thesevariablesprovideacombination ofmeans,extremesandseasonalitythatareknowntoinÃŸuencespeciesdistribution(Root etal., 2003)andweselected onlyvariablesthatwerenotcollinear(pair-wiserPearson< 0.75). Inthecaseoffreshwaterspecies,manystudieshaverevealed strongcorrelationsbetweenspatialpatternsandclimatic variables(Jocque etal. ,2010),mostlytemperatureandthe availabilityofwater,andhaveusedspeciesdistributionsmodelstosuccessfullypredictthedistributionofÃžshes(McNyset, 2005)andmussels(Drake&Bossenbroek,2004).Future climatedatawereextractedfromtheGlobalClimateModel dataportal(http://www.ccafs-climate.org/spatial_downscaling/).Thesemodelswerestatisticallydownscaledfromthe originalGlobalChangeModeloutputswiththeDeltamethod (Ramirez-Villegas&Jarvis,2010).Duetolargeeffectsofdifferentatmosphereoceanglobalcirculationmodels(AOGCMs) onspeciesrangeprojections,simulationsoffutureclimate werebasedonthreedifferentAOGCMs(HADCM3,CSIRO2 andCGCM2)averagedfrom2040to2069(Ã”2050')and2070to 2099(Ã”2080').Weusedtwodifferentscenarios(A1B,B2A)that reÃŸectdifferentassumptionsaboutdemographic,socioeconomicandtechnologicaldevelopmentongreenhousegas emission(Solomon etal., 2007).A1Bscenariorepresentsa maximumenergyrequirement,emissionsbalancedacross fossilandnon-fossilsourcesandB2Arepresentsalower energyrequirementandthusloweremissionsscenariothan A1B(Solomon etal., 2007).Landusedata.Currentandfuturegloballanduseandland covervariablesweresimulatedbytheGlobio3landmodelata 0.5 Â° resolutionfortwodifferentemissionscenariosA1Band B2A(MillenniumEcosystemAssessment etal. ,2005;Alkemade etal. ,2009).Thesedatatogetherwithclimatewereused tomodelthepotentialdistributionofthespeciesinthe 100 worldÂ’sworstinvasivespecies list(seebelow).Forthetwo selectedemissionscenarios,were-classiÃžedthe30different landcovertypesfromtheGlobio3data(Bartholom e&Belward,2005)into12landcovertypevariablesbygrouping someofthemtogether.Theselandusevariablesconsistedof theproportionofthegridcellcoveredby(i)treecover,(ii)tree coverregularlyÃŸooded,(iii)mosaichabitat,(iv)treecover burnt,(v)shrubcover,(vi)herbaceouscover,(vii)cultivated andmanagedareas,(viii)bareareas,(ix)waterbodies,(x) snowandice,(xi)artiÃžcialsurfacesandassociatedareasand (xii)pasture.Wecalculatedforeachpixeltheproportionof eachlandcovertypein1970 Â– 2000(Ã”current'),Ã”2050'and Ã”2100'.Biomedata.Weused14differenttypeofbiomes:(i)boreal forest,(ii)coolconiferousforest,(iii)grasslandandsteppe, (iv)hotdesert,(v)ice,(vi)savanna,(vii)scrubland,(viii)temperatedeciduousforest,(ix)temperatemixedforest,(x)tropicalforest,(xi)tropicalwoodland,(xii)tundra,(xiii)warm mixedforest,and(xiv)woodedtundra,thatweextractedfrom theIMAGE2.4modelforeach0.5 Â° cell(Leemans&Born, 1994;Prentice etal., 1992).Thebiomedatawereusedtocomparethefuturepotentialnumberofinvasivealienspeciesper biome.Invasivealienspeciesdata.Wecollectedcurrentdistribution dataforthespeciesonthelist 100oftheworldÂ’sworstinvasive alienspecies ,compiledbytheInternationalUnionfortheConservationofNature(IUCN,Lowe etal. ,2000).Developedin 2000bytheISSGglobalnetworkofover1000invasionbiology experts,thissynthesisincludedinputfromthewidercommunityofpractitionersandscientistswithexpertiseonalltaxonomicgroupsandenvironments.Thelistprovidesthemost geographicallyandtaxonomicallyrepresentativesetofthe mostdangerousinvasivealienspeciesaroundtheworld,causingsigniÃžcantimpactsonbiodiversityand/orhumanactivity inallecosystems. Wechosethese100speciesinanattempttoobjectively explorepatternsofchange(i.e.,rangeexpansionversusretractions)andgeographicpatterns(i.e.,intosomeregionsandbiomesbutnotothers)fordifferenttaxonomicgroups.They sharethefollowingspeciÃžcations:(i)largeimpactonbiodiversityand/orhumanactivity,(ii)threatenavarietyoftaxonomicgroups,ecosystems,typesofimpacts;(iii)illustrationof importantissuessurroundingbiologicalinvasions.Thislist includesthreemicro-organisms,Ãžvemacro-fungi,fouraquatic plants,30terrestrialplants,nineaquaticinvertebrates,17terrestrialinvertebrates,threeamphibians,eightÃžshes,three birds,tworeptilesand14mammals(Lowe etal. ,2000).Rinderpestviruswasremovedfromthelistofthe100becauseit isnoweradicated.Wemadeanextensivesearchforrecords fromboththenativeandinvadedrangesasrecommendedbyÂ© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã3748GLOBALCHANGEANDBIOLOGICALINVASIONS 3741
Gallien etal. (2010)forallthe99species.Datawerecollected fromavarietyofonlinedatabases,referencesandpersonal communications(TableS2fordetails). Wecollectedonaverage3850recordsperspecieswitha minimumof46recordsfortheleastdocumentedspecies.We foundrecordsofthe99speciesfromallovertheworld(except inSahararegion,northeasternRussia,northernCanadaand Greenland).SpeciesdistributionmodelprojectionsModelingprocess.Wemodeledthepotentialdistributionof the99invasivespeciesbycombiningavailableoccurrences withasetofsixclimaticvariablesand12landusevariables thatweassumedtobeimportantforinvasivespecies.Analysisoftheclimateandlandusepreferencesofaspeciescan thereforebeusedtopredictareaswherethespeciescould occuratglobalscales.Althoughotherfactorssuchassoil propertiesormicro-climatealsodeterminethepresenceor absenceofaspeciesatthelocalscale,weassumedthatclimate andlandusewerethemostimportantexplanatoryvariables ofspeciesdistributionattheglobalscale.WeusedsixdifferentSDMs,withinthebiomodv.2.0platform(Thuiller etal., 2009)carriedoutontheRplatform.Thesemodelswere:GeneralizedLinearModel,GeneralizedBoostingTrees,MultivariateAdaptiveRegressionSplines,RandomForest,Flexible DiscriminantAnalysisandMaximumEntropy.Moredetails abouttheÃžrstÃžvemodelingtechniquescanbefoundinThuiller etal., (2009)andinElith etal. (2011)forMaximum Entropy.Allmodelsrequiredpresenceandpseudo-absences (PAsorbackground).FivesetsofPAsweregeneratedby selectingfrom1000to10000randompointsacrosstheglobe, accordingtothenumberofpresences N (if N 1000then1000 PAswereselected,else10,000PAswereselected)[asrecommendedbyBarbet-Massin etal. (2012)].Equalweightings weregiventopresencesandPAs.Evaluatingmodelperformance.Weevaluatedthepredictive performanceofeachmodelusingarepeatedsplitsampling approachinwhichmodelswerecalibratedover70%ofthe dataandevaluatedovertheremaining30%.Thisprocedure wasrepeatedfourtimes.Weusedtwodifferentstatisticalmetrics:thetrueskillstatistics(TSS)(Allouche etal. ,2006)and AreaUndertheROCCurve(AUC)(Fielding&Bell,1997). TheTSSaccountsforbothomissionandcommissionerrors, andrangesfrom 1to + 1,where + 1indicatesperfectagreementand0representsarandomÃžt(Allouche etal. ,2006). AUCvaluesrangefrom0to1,andaccordingtoSwets(1988), anAUCabove0.8isconsideredtohaveÃ”good'discrimination abilities.Allcalibratedmodelsperformedverywellwithan averageAUCvalueof0.983 0.002andanaverageTSSvalue of0.911 0.007(Fig.S1).WealsousedtheBoyceindexto assessmodelperformance(Boyce etal. ,2002;Petitpierre etal. , 2012).TheBoyceindexonlyrequirespresencedata,where AUCandTSSrequirebothpresenceandabsencedata.Boyce indexmeasureshowmuchmodelpredictionsdifferfromrandomdistributionoftheobservedpresencesacrossthepredictiongradients.ValuesofBoyceindexvarybetween 1and + 1.Positivevaluesindicateamodelwithpresentpredictions thatareconsistentwiththedistributionofpresencesinthe evaluationdataset;valuesclosetozeromeanthatthemodelis notdifferentfromarandommodel.WecalculatedtheBoyce indexforeachofthe60models(GLM,MARSandMaXent) perspecies.Onaverage,MARS(0.819 0.322)andMaXent (0.817 0.225)gaveaverygoodevaluationmeasure,whereas GLM(0.367 0.286)waslessrobust,butstillgavefairpredictionsbasedontheBoyceindex.Thismakestheinterpretation ofourresultsconsistentoverallspecies.Ensemblemodelingapproach.TheÃžnalcalibrationofevery modelforgeneratinginvasionscenariosused100%ofavailabledata.Weusedanensembleforecastapproachtoaccount forthevariabilityamongthesixspeciesdistributionmodels andthethreegeneralcirculationmodelstogetthecentraltendency(Ara ujo&New,2007).Tomakesurenospuriousmodelswereusedintheensembleprojections,weonlykeptthe projectionsforwhichthemodel'sevaluationestimatedby AUCandTSSwerehigherthan0.8and0.6,respectively(e.g., Gallien etal. ,2012),andaweightproportionaltotheirTSS evaluationwasassociatedwitheachmodel.Becauseofthe potentialproblemsraisedbyLobo etal. (2008)ontheuseof AUCasameasureofmodelperformance,wedecidedtouse TSSfortheÃžnalconsensusdistributions.TheÃžnalcurrentand futureconsensusdistributionswereobtainedbycalculating theweightedmeanofthedistributionforeachscenario (Marmion etal., 2009).Thisresultedinonecurrentprobability distributionmapandthreefutureprobabilitydistribution maps(becauseweusedthreeglobalcirculationmodels)for eachemissionscenario(A1BandB2A)andeachspecies. Futureprobabilitymapswerethereforeaveragedforeachscenario.Then,wetransformedtheprobabilitymapsobtained fromtheensembleprojectionsintobinarysuitable/non-suitablemapsusingthethresholdmaximisingtheTrueSkillStatistics,asproposedbyAllouche etal. (2006).Thiswasdoneto ensurethemostaccuratepredictionssinceitisbasedonboth sensitivityandspeciÃžcity(Jim enez-Valverde&Lobo,2007). Weobtainedonecurrentbinarydistributionmapandthree futurebinarydistributionmapsperemissionscenarioandper species.Consensusbinarymapswereobtainedattributing presencewhenthemajorityofGCMs(i.e.,twoofthree)predictedpresence,otherwisepredictingabsence.Sinceprojectionswerenotbasedonanequal-areaprojectionsystem,cell sizesdecreasepole-ward.Therefore,wecalculatedtheareaof eachcellandweightedthecellsoftheworldmapbytheir area.ResultsFuturehotspotsofinvasion(i.e., > 60invasivealienspecies)wereprojectedtomostlyoccurineasternUnited States,northeasternEurope,southwestAustraliaand NewZealand.IndonesianandPaciÃžcislandsregion, centralAfrica,andsouthernBrazilcouldbeaffectedat alowerrate(i.e.,20 Â– 40invasivealienspecies),regardlessofthetime-sliceorclimatescenarioused(Fig.1a).Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã37483742 C.BELLARD etal.
Changesoffuturenumberofinvasivealienspecies showedimportantgeographicvariation,allowingfor thedetectionofareasmorevulnerabletoinvasionsand thosethatmightactuallyloseinvasivealienspecies. Underallscenarios,anincreaseinthenumberofinvasivealienspecieswasprojectedfornorthwesternEuropeandnortheasternUnitedStates,Indiaandeastern China(Fig.1b).Onthecontrary,adecreaseinthenumberofinvasivealienspecieswasprojectedforCentral andSouthAmerica,southwesternEurope,central Africa,andIndonesianandPaciÃžcislandsregions,easternAustralia.Globally,mostareasprojectedtoincrease inthenumberofinvasivealienspeciesarelocatedin continentalandtemperateclimaticzones,especiallyin thenorthernhemisphere,whilethepotentialnumberof invasivealienspecieslargelydecreasedinthetropical regionsatlowlatitudes.Climateandlandusechanges couldcreateopportunitiesformanytemperatespecies tospreadathigherlatitudesbutcouldalsoleadtoa signiÃžcantlostoftropicalinvasivealienspecies.For example,severalinvasivealienspecieswereprojected toexpandtheirrangesintomoretemperateregionsin northernEurope(Fig.1b).Globally,thenumberof invasivealienspeciessusceptibletoinvadenewregions inthefuturetendedbothtobehigherinthenorthern hemispherecomparedtothesouthern,andtodecrease atlowerlatitudes(Fig.1a). Moreprecisely,ouranalysesrevealedthatbiomes harboringextremeclimaticconditionssuchasice,hot desert,tundraandwoodedtundrawerenotpredicted tobesuitableforinvasivealienspeciesby2100(Fig.2 andTableS3).Otherbiomestendedtohavesuitable environmentalconditionsforahighnumberofinvasive alienspeciesinthefuture,especiallytemperatedeciduousforests(27,averagenumberofinvasivealienspeciesperpixel),warmmixedforest(22),temperate mixedforest(16)andtropicalforestandwoodland(12) (TableS3).Thehighestincreaseofinvasivealienspecies,amongthe14typesofterrestrialbiomes,wasprojectedtooccurintemperatemixedforests( + 4.5%,i.e., averageinvasivealienspeciesperpixel),followedby coolconiferousforests( + 3.4%),whereastropicalforests ( 4%)andtropicalwoodlands( 4.4%)mightbecome suitableforalowernumberofinvasivealienspeciesin thefuture.Inotherwords,biomesexpectedtoshiftinto futureextremeclimaticzones(e.g.,tropicalforest)were (a) (b) (c) Fig.1 Globaldistributionofinvasivespeciesundercurrentandfuturescenarios.(a)Projectedrichnessininvasivespeciesby2000, (b)Relativechangeininvasivespeciesrichnessbetween2000and2100and(c)Projectedrichnessininvasivespeciesby2100. Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã3748GLOBALCHANGEANDBIOLOGICALINVASIONS 3743
predictedtoloseinvasivealienspecies,whereasbiomes (e.g.,temperatemixedforest)thatoccurredathigher latitudes,wheretheclimatewillbelessextreme,were predictedtogainsomeinvasivealienspecies. Amongthe100invasivealienspecies,rangesize expandedonaveragefrom2to6%forbothCO2emissionscenarios(TableS4).However,thisslightincrease maskedhighvariationacrosstaxonomicgroups: amphibians( 65%),birds( 24%),andfungi( 11%) couldexperiencestrongrangesizeshrinkageunder futureprojections(Fig.3).Rangesizedistributionof Ãžshes( 1%),mammals( 4%)andreptiles( 4%)were predictedtoremainstable,whileaquaticinvertebrates ( + 59%),aquaticplants( + 12%),micro-organisms( + 17%), andterrestrialinvertebrates( + 18%)werepredictedto largelyexpandtheirpotentialrangedistributions. Whileourresultspredictedconvergentpatternsof rangesizechangewithinamphibiansandmicro-organisms(i.e.,eithershrinkorexpand),divergentpatterns wereobservedwithinthemajorityoftheothergroups, particularlywithinterrestrialinvertebrates,plants,and fungi(Fig.4).DiscussionUsingstate-of-the-artofspeciesdistributionmodels, ourÃžndingsidentifythreefuturehotspotsofinvasion: Europe,northwesternNorthAmerica,andSouthAustraliaandNewZealand,whatevertheclimatescenario used.Globally,thenumberofinvasivealienspeciesin thefuturetendedtobehigherinthenorthernhemispherecomparedtothesouthernandtodecreaseat lowerlatitudes.Manystudiessuggestthatglobal changewill,onaverage,increasetheriskofinvasion (Walther etal. ,2009;Bradley etal. ,2012).Surprisingly, wedidnotÃžndaglobalincreaseininvasivespecies distributionsfollowingclimateandlandusechanges. Wefoundcontrastingprojectedchangesinspeciesdistributionsamongregionsandtaxa.Forexample,CentralAmerica,northernSouthAmerica,WesternEurope (e.g.,Portugal,SpainandFrance),centralAfrica,easternAustralia,andIndonesiaallshowedadecreasein theexpectednumberoffutureinvasivealienspecies. Wealsoshowedconsistentexpecteddistribution shrinkageforinvasiveamphibiansandbirds,anda substantialdistributionincreasesformostaquaticand terrestrialinvertebrates.TherangesizesforÃžshes, mammals,andreptilesareexpectedtoremainstableon average,althoughweobservedsomelocalshiftsin speciesareadistributions. Althoughourapproachhasmerits,wealsofaced limitationsthatcallforfurtherreÃžnements.First,our resultsshouldbeinterpretedwithrespecttotheseinvasivealienspeciesonly,astheyarenotarepresentative sampleofallglobalinvasivealienspecies(i.e.,theyare mostlyinvasiveintemperateareas).Despitethissamplebias,these100invasivealienspeciesincludesome ofthemostharmfulandwidespreadinvasivealien speciesintheworld,andtheyhavealreadydemonstratedtheirabilitytoestablishandspreadintonew (a) (b) Fig.2 Effectofclimateandlandusechangesonthenumberofinvasivespeciesperpixelineachbiome.(a)Maprepresentingthebiomesand(b)theassociatedboxplotsrepresentingthenetpotentialchangesofinvasivespeciesnumberbetween2000and2100,under theA1Bemissionscenarios. Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã37483744 C.BELLARD etal.
ecosystems.Therefore,theexpansionoftheseinvasive alienspecieswillresultinnewecologicalinteractions withconsequencesthatareoftenhardtopredict,but arelikelytobenegativefornativeecosystems,economiesandhumanhealth(Simberloff etal., 2012).In addition,newinvasivealienspeciesarealsoexpected toemergeasaconsequenceoftheongoingclimateand landusechanges(Hellmann etal. ,2008).However,the rangecontractionswehavepredictedforsomeofthese dangerousinvasivealienspeciesshouldprovidesome goodnewsforthoseconcernedwiththeirmanagement anderadication.Infact,reducedclimaticsuitabilityon currentlyinvadedareasmaymakeinvasivespeciesless competitive,thereforepotentiallyleadingtoretreat (Pyke etal., 2008;Bradley etal. ,2009). Fig.3 Rangesizechangeforthedifferenttaxonomicgroupsofthe100invasivespecies.Boxplotoftheeffectofclimateandlanduse changesoninvasivealienspeciesrangesize(estimatedbycountingthenumberofsuitablepixels)underA1Bscenarioforeachspecies sortedbytaxonomicgroup. Fig.4 Temporalrangesizechangeforthe100invasivealienspeciesamongthedifferenttaxonomicgroups.Effectofclimateandland usechangesonrangesize(estimatedbycountingthenumberofsuitablepixels)underA1Bscenarioforeachspeciesalongthedifferent time-slices.Smoothingwasperformedforeachspeciesusinglinearregression. Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã3748GLOBALCHANGEANDBIOLOGICALINVASIONS 3745
Weareawarethatthemethodologyofprojectingspeciesdistributionsintothefutureisknowntobelimited bytheamountofinformationabletobeincorporatedin themodels(Schwartz,2012).Likewise,inourstudy,climateandlanduseareassumedtobetheonlydrivers ofchangefortheseinvasivealienspeciesdistributions. Weonlyconsideredabioticvariables,ouranalysesdisregardeddispersalcapacities,bioticinteractions,and opportunityofinvasivealienspeciesintroduction(Gaston&Fuller,2009).Recentstudiesprovidedstrongevidencethatbioticandabioticfactorsaredeterminantsin thepatternofinvasivealienspecies(Roura-Pascual etal., 2011;Gallardo&Aldridge,2013).Thepotential presenceofsuitableenvironmentalconditionsfora Ã”new'speciesdoesnotautomaticallyleadtosuccessful establishment,meaningSDMsmayoftenoverestimate thefullextentofpredictedinvasions.Speciesmusttravelacrossmajorgeographicbarrierstotheirnewlocation,andtheymustsurviveandtolerateenvironmental andbioticconditionsatthearrivalsite.However,these cannotpresentlybeincorporatedintoouranalyses. ResultsofSDMsarealsopotentiallylimitedintheir abilitytopredictspeciesoccurrencesinnovelenvironmentalspace,becausewecouldnotforecastifspecies willorwillnotoccupythenewconditionsthatwere notavailabletothembefore.Finally,weassumethat invasivealienspeciesareinequilibriumwiththeir environment,whichisnotnecessarythecaseasmany invasivealienspecieshaverecentlybeenintroduced intonewecosystems. Acarefulinvestigationofsomemethodological uncertaintiesinourstudiesconÃžrmstheconsistencyof ourÃžndings(seeMethods).Theresultsfromthethree differentglobalcirculationmodelsatthetwodifferent periods(i.e.,2050and2100)areconsistent,supporting ourmainconclusions. Here,weshowfortheÃžrsttimethatthemagnitude andthepatternofinvasionaroundtheworldisprojectedtochangeinthe21stcenturyforalargesample ofinvasivealienspecies,followingexpectedchangesin climateandlanduse.Ourprojectionsshowthatthe numberofinvasivealienspeciesshouldincreasein northeasternEuropeandnortheasternUnitedStates morethanelsewhere.Theseresultingmapsindicating futurehotspotsofinvasionhelppointtoglobalzonesin whichemphasisshouldbeplacedonpreventionand earlydetection,fortheprotectionoffuturebiodiversity intheseareas.Wealsoclearlyshowedthatsome regions(i.e.,atlowerlatitudes)willloseinvasivealien species.Thepotentialabsenceofsuitableconditionsfor aninvasivealienspeciesisoneofthestrongerÃžndings sinceitisbasedonrealpresenceinthecurrentdistribution.Thisresultcouldbeexplainedbothbecausethese regionswillsufferfromextremeclimateconditionsfor invasivealienspecies(Beaumont etal. ,2010;Neelin etal., 2006)andfutureimportantlocalclimatechanges havebeenshowntooccuratlowlatitudes,including theCaribbean/CentralAmericaregionandequatorial SouthAmerica(Williams etal., 2007).Habitatdegradationthroughdeforestationwasalsoprojectedto increaseintropicalregions(Laurance etal. ,2012). Additionally,ithasbeenshownthattropicalregions mightbecomeextremelysensitivetoclimatechange becausetheincreaseinabsolutetemperaturesrelative tothepastvariabilityisrelativelylargecomparedto temperateregions(Beaumont etal. ,2010).Theseresults areofprimaryimportanceasitsuggeststhatsomeinvasivealienspeciescouldsufferfromclimateandland usechanges.Thesepotentiallocalextinctionscouldcreaterestorationopportunitiesforsomeregionssuchas CentralAmericaorsoutheastofAustraliabecausemanagementofinvasivealienspeciescouldbeeasierfor speciesthatarecurrentlyatthelimitoftheirabiotictolerance.Globally,ourresultssuggeststronglythatbiologicalcommunitieswillseeimportantreorganizations inthefutureowingtoshiftingareadistributionofmany invasivealienspecies.SDMsarecosteffective,giving theopportunitytoprioritizeandfocalizeactions includingÃžnancialinvestmentsforcertainregions.Our resultsprovidevaluableinsightsofplausibleandpossiblefuturehotspotsofinvasions.Theyalsohighlightthe needtoaccountforbothclimateandlandusechange whenfocusingonbioticexchanges.Overall,thegeneral picturepaintedhereisthatthequestionofwhetherclimateandlandusechangeswillfavorinvasivealien speciesisnotlikelytohaveasimpleuniversalanswer. Toconclude,weprovideanewpictureoffuture invasions,highlightingthatresponsesofinvasivealien speciestoglobalchangewilldependbothontheregion consideredandonthetaxaconsidered.Theseresults areofmajorimportanceforEurope,northeastUnited States,CentralAmericaandAfrica,Indonesianand PaciÃžcislandsregionsbecausesuitabilityofthese regionstoinvasivealienspeciescouldbestronglymodify.Theimpactsoftheseinvasivealienspeciesonthese regionsmightbecomeevenmoreimportantinthe future.Wesuggestthatpromptresponsestotheintroductionofinvasivealienspeciesandcontrolofinvasionsshouldbeakeycomponentoftheglobaleffortsto mitigatetheeffectsofclimatechange.Governments shouldalsoregulatetheimportationofspeciesthrough black-listing,andactivateearlywarningandrapid responseframeworks,sincesuchactionsaredecisivein preventinginvasionsandecologicallylessriskythan postponedinterventions(Simberloff etal., 2012). Finally,ourmodelspredictthatrestorationopportunitiesresultingfromclimatechangewillexistinthe future.EradicationandcontrolprogramsshouldÂ© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã37483746 C.BELLARD etal.
becontinuedforinvasivealienspeciesthatwill sufferfromglobalchanges,butalsoencouragedbyour Ãžndings.AcknowledgementsThearticlewaswrittenwhiletheauthorsweresupportedby variousgrants,CBfromtheCNRS(PhDcontract),FCandWT fromtheFrenchÃ”AgenceNationaledelaRecherche'(ANR)with theRARE(2009PEXT01001)andSCION(ANR-08-PEXT-03) projects.IthasalsobeensupportedbyanEuropeanprogramBIODIVERSA:FFII.WTreceivedalsofundingfromtheEuropean ResearchCouncilundertheEuropeanCommunity'sSeven FrameworkProgrammeFP7/2007-2013GrantAgreementno. 281422(TEEMBIO).WethankGloriaLuqueandElsaBonnaud forconstructivecriticismanddiscussionsonanearlierversion ofthemanuscript.WealsothankJoshDonlanandJessica AlbateforEnglishcorrectionsonthemanuscript.Wegratefully acknowledgeusefulcommentsfromtheanonymousreferees thatimprovedthedifferentversionofthemanuscript.Weare alsogratefultothemanycolleagueswhoprovidedspecies occurrencesdata(seeTableS2fordetails).Allco-authorshave noconÃŸictofinteresttodeclare.ReferencesAlkemadeR,OorschotM,MilesL,NellemannC,BakkenesM,TenBrinkB(2009) GLOBIO3:aframeworktoinvestigateoptionsforreducingglobalterrestrialbiodiversityloss. Ecosystems , 12 ,374 Â– 390. AlloucheO,TsoarA,KadmonR(2006)Assessingtheaccuracyofspeciesdistribution models:prevalence,kappaandthetrueskillstatistic(TSS). JournalofAppliedEcology , 46 ,1223 Â– 1232. Ara ujoMB,NewM(2007)Ensembleforecastingofspeciesdistributions. Trendsin ecology&evolution , 22 ,42 Â– 47. Barbet-MassinM,JiguetF,AlbertCH,ThuillerW(2012)Selectingpseudo-absences forspeciesdistributionmodels:how,whereandhowmany? MethodsinEcology andEvolution , 3 ,327 Â– 338. Bartholom eE,BelwardAS(2005)GLC2000:anewapproachtogloballandcover mappingfromEarthobservationdata. InternationalJournalofRemoteSensing , 26 , 1959 Â– 1977. BeaumontLJ,PitmanA,PerkinsS,ZimmermannNE,YoccozNG,ThuillerW (2010)Impactsofclimatechangeontheworld'smostexceptionalecoregions. ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica , 108 , 2306 Â– 2311. BoyceMS,VernierPR,NielsenSE,SchmiegelowFKA(2002)Evaluatingresource selectionfunctions. EcologicalModelling , 157 ,281 Â– 300. BradleyB,OppenheimerM,WilcoveDS(2009)Climatechangeandplantinvasions: restorationopportunitiesahead? GlobalChangeBiology , 15 ,1511 Â– 1521. BradleyBA,BlumenthalDM,EarlyR etal. (2012)Globalchange,globaltrade,and thenextwaveofplantinvasions. FrontiersinEcologyandtheEnvironment , 10 , 20 Â– 28. BrookBW,SodhiNS,BradshawCJ(2008)Synergiesamongextinctiondriversunder globalchange. TrendsinEcology&Evolution , 23 ,453 Â– 460. ButchartSH,WalpoleM,CollenBI etal. (2010)Globalbiodiversity:indicatorsof recentdeclines. Science , 328 ,1164 Â–1168. ButchartSHM,ScharlemannJPW,EvansMI etal. (2012)Protectingimportantsites forbiodiversitycontributestomeetingglobalconservationtargets. PLoSONE , 7 , e32529. DiezJM,D'AntonioCM,DukesJS etal. (2012)Willextremeclimaticeventsfacilitate biologicalinvasions? FrontiersinEcologyandtheEnvironment , 10 ,249 Â– 257. DrakeJM,BossenbroekJM(2004)Thepotentialdistributionofzebramusselsinthe UnitedStates. BioScience , 54 ,931. ElithJ,PhillipsSJ,HastieT,DudÃµM,Dud ÃµkM,CheeYE,YatesCJ(2011)Astatistical explanationofMaxEntforecologists. DiversityandDistributions , 17 ,43 Â– 57. EsslF,DullingerS,RabitschW etal. (2011)Socioeconomiclegacyyieldsaninvasion debt. ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica , 108 ,203 Â– 207. FicetolaGF,ThuillerW,MiaudC(2007)Predictionandvalidationofthepotential globaldistributionofaproblematicalieninvasivespecies-theAmericanbullfrog. DiversityandDistributions , 13 ,476 Â– 485. FieldingAH,BellJF(1997)Areviewofmethodsfortheassessmentofpredictionerrors inconservationpresence/absencemodels. EnvironmentalConservation , 24 ,38 Â– 49. FoleyJA,DefriesR,AsnerGP etal. (2005)Globalconsequencesoflanduse. Science , 309 ,570 Â– 574. GallardoB,AldridgeDC(2013)The"dirtydozen":socio-economicfactorsamplify theinvasionpotentialof12high-riskaquaticinvasivespeciesinGreatBritainand Ireland. JournalofAppliedEcology , 50 ,757 Â– 766. GallienL,M Â unkem Â ullerT,AlbertCH,BoulangeatI,ThuillerW(2010)Predicting potentialdistributionsofinvasivespecies:wheretogofromhere? Diversityand Distributions , 16 ,331 Â– 342. GallienL,DouzetR,PratteS,ZimmermannNE,ThuillerW(2012)Invasivespecies distributionmodels-howviolatingtheequilibriumassumptioncancreatenew insights. GlobalEcologyandBiogeography , 21 ,1126 Â–1136. GastonKJ,FullerR(2009)Thesizesofspecies'geographicranges. JournalofApplied Ecology , 46 ,1 Â– 9. HellmannJJ,ByersJE,BiderwagenBG,DukesJS(2008)Fivepotentialconsequences ofclimatechangeforinvasivespecies. ConservationBiology , 22 ,534 Â– 543. HijmansRJ,CameronSE,ParraJL,JonesPG,JarvisA(2005)Veryhighresolution interpolatedclimatesurfacesforgloballandareas. InternationalJournalofClimatology , 25 ,1965 Â– 1978. JetzW,WilcoveDS,DobsonAP(2007)Projectedimpactsofclimateandland-use changeontheglobaldiversityofbirds. PLoSbiology , 5 ,e157. Jim enez-ValverdeA,LoboJM(2007)Thresholdcriteriaforconversionofprobability ofspeciespresencetoeither Â– orpresence Â– absence. ActaOecologica , 31 ,361 Â– 369. Jim enez-ValverdeA,PetersonAT,Sober onJ,OvertonJM,Arag onP,LoboJM(2011) Useofnichemodelsininvasivespeciesriskassessments. BiologicalInvasions , 13 , 2785 Â– 2797. JocqueM,FieldR,BrendonckL,DeMeesterL(2010)Climaticcontrolofdispersalecologicalspecializationtrade-offs:ametacommunityprocessattheheartofthe latitudinaldiversitygradient? GlobalEcologyandBiogeography , 19 ,244 Â– 252. LarsonER,OldenJD(2012)Usingavatarspeciestomodelthepotentialdistribution ofemerginginvaders. GlobalEcologyandBiogeography , 21 ,1114 Â– 1125. LauranceWF,CarolinaUsecheD,RendeiroJ etal. (2012)Avertingbiodiversity collapseintropicalforestprotectedareas. Nature , 489 ,290 Â– 294. LeemansR,BornGJ(1994)Determiningthepotentialdistributionofvegetation,crops andagriculturalproductivity. Water,Air,&SoilPollution , 76 ,133 Â– 161. LeroyB,PaschettaM,CanardA,BakkenesM,IsaiaM,YsnelF(2013)Firstassessmentofeffectsofglobalchangeonthreatenedspiders:Potentialimpactson Dolomedesplantarius(Clerck)anditsconservationplans. BiologicalConservation , 161,155 Â– 163. LoboJM,Jim enez-ValverdeA,RealR(2008)AUC:amisleadingmeasureoftheperformanceofpredictivedistributionmodels. GlobalEcologyandBiogeography , 17 ,145 Â– 151. LoweS,BrowneM,BoudjelasS,DePoorterM(2000) 100oftheWorldÂ’sWorstInvasive AlienSpeciesAselectionfromtheGlobalInvasiveSpeciesDatabase .TheInvasiveSpeciesSpecialistGroup(ISSG)aspecialistgroupoftheSpeciesSurvivalCommission (SSC)oftheWorldConservationUnion(IUCN),Auckland. MarmionM,ParviainenM,LuotoM,HeikkinenRK,ThuillerW(2009)Evaluationof consensusmethodsinpredictivespeciesdistributionmodelling. DiversityandDistributions , 15 ,59 Â– 69. McNysetKM(2005)Useofecologicalnichemodellingtopredictdistributionsof freshwaterÃžshspeciesinKansas. EcologyofFreshwaterFish , 14 ,243 Â– 255. MillenniumEcosystemAssessment,ReidWV,MooneyHA etal. (2005) Ecosystems andHumanWell-being:Synthesis .IslandPress,Washington,DC. MurrayJV,StokesKE,KlinkenRD(2012)Predictingthepotentialdistributionofa riparianinvasiveplant:theeffectsofchangingclimate,ÃŸoodregimesandlandusepatterns. GlobalChangeBiology , 18 ,1738 Â– 1753. NeelinJD,M Â unnichM,SuH,MeyersonJE,HollowayCE(2006)Tropicaldrying trendsinglobalwarmingmodelsandobservations. ProceedingsoftheNational AcademyofSciencesoftheUnitedStatesofAmerica , 103 ,6110 Â– 6115. O'DonnellJ,GallagherRV,WilsonPD,DowneyPO,HughesL,LeishmanMR(2012) Invasionhotspotsfornon-nativeplantsinAustraliaundercurrentandfutureclimates. GlobalChangeBiology , 18 ,617 Â– 629. PetitpierreB,KuefferC,BroennimannO,RandinC,DaehlerC,GuisanA(2012) Climaticnicheshiftsarerareamongterrestrialplantinvaders. Science , 335 , 1344 Â– 1348. PrenticeI,CramerW,HarrisonS,LeemansR,MonserudR,SolomonA(1992)Aglobalbiomemodelbasedonplantphysiologyanddominance,soilpropertiesand climate. JournalofBiogeography , 19 ,117 Â– 134.Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã3748GLOBALCHANGEANDBIOLOGICALINVASIONS 3747
PykeCR,ThomasR,PorterRD,HellmannJJ,DukesJS,LodgeDM,ChavarriaG (2008)Currentpracticesandfutureopportunitiesforpolicyonclimatechangeand invasivespecies. Conservationbiology:thejournaloftheSocietyforConservationBiology , 22 ,585 Â– 592. Ramirez-VillegasJ,JarvisA(2010) DownscalingGlobalCirculationModelOutputs:The DeltaMethodDecisionandPolicyAnalysisWorkingPaperNo.1 .InternationalCenter forTropicalAgriculture,CIAT,Cali,Colombia. RootTL,PriceJT,HallKR,SchneiderSH(2003)Fingerprintsofglobalwarmingon wildanimalsandplants. Nature , 421 ,57 Â– 60. Roura-PascualN,HuiC,IkedaT etal. (2011)Relativerolesofclimaticsuitabilityand anthropogenicinÃŸuenceindeterminingthepatternofspreadinaglobalinvader. ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica , 108 , 220 Â– 225. SchwartzMW(2012)Usingnichemodelswithclimateprojectionstoinformconservationmanagementdecisions. BiologicalConservation , 155 ,149 Â– 156. SimberloffD,MartinJ-L,GenovesiP etal. (2012)Impactsofbiologicalinvasions: what'swhatandthewayforward. TrendsinEcology&Evolution , 28 ,58 Â– 66. SolomonS,QinD,ManningM etal. (2007) ContributionofWorkingGroupItothe FourthAssessmentReportoftheIntergovernmentalPanelonClimateChange .CambridgeUniversityPress,UnitedKingdomandNewYork,NY,USA. SwetsJA(1988)Measuringtheaccuracyofdiagnosticsystems. Science , 240 , 1285 Â– 1293. ThuillerW,LafourcadeB,EnglerR,Ara ujoMB(2009)BIOMOD-aplatformfor ensembleforecastingofspeciesdistributions. Ecography , 32 ,369 Â– 373. WaltherG-R,RoquesA,HulmePE,SykesMT,PysekP etal. (2009)Alienspeciesina warmerworld:risksandopportunities. Trendsinecology&evolution , 24 ,686 Â– 693. WilliamsJW,JacksonST,KutzbachJE(2007)Projecteddistributionsofnovelanddisappearingclimatesby2100AD. ProceedingsoftheNationalAcademyofSciencesofthe UnitedStatesofAmerica , 104 ,5738 Â– 5742.SupportingInformationAdditionalSupportingInformationmaybefoundinthe onlineversionofthisarticle: FigureS1 .BoxplotsofTSSandanaverageAreaUnderthe operatingcharacteristicCurveinaROCanalysisvaluesfor allthecalibratedmodels. TableS1 .Environmentalvariableslist. TableS2 .Listofthe100casesoftheworld'sworstinvasive specieswithdatasourcesandnumberofoccurrences. TableS3 .PercentageofnetchangeofthenumberofIASfor the14typesofbiomesundertheA1BandB2scenarios. TableS4 .Percentageofnetchangebetweencurrentand futurescenarios(A1BandB2)oftherangesizeforthedifferenttaxa.Â© 2013JohnWiley&SonsLtd, GlobalChangeBiology , 19 ,3740Ã37483748 C.BELLARD etal.