BioControl (2012) 57:235–246 DOI 10.1007/s10526-011-9399-x
Finalizing host range determination of a weed biological control pathogen with best linear unbiased predictors and damage assessment Dana K. Berner • Craig A. Cavin
Received: 1 March 2011 / Accepted: 27 July 2011 / Published online: 13 August 2011 Ó International Organization for Biological Control (outside the USA) 2011
Abstract Colletotrichum gloeosporioides f. sp. salsolae (Penz.) Penz. & Sacc. in Penz. (CGS) is a facultative parasitic fungus being evaluated as a classical biological control agent of Russian thistle or tumbleweed (Salsola tragus L.). In initial host range determination tests, Henderson’s mixed model equations (MME) were used to generate best linear unbiased predictors (BLUPs) of disease severity reaction to CGS among 89 species of plants related to S. tragus. The MME provided: (1) disease assessments for rare and difficult or impossible to grow species, (2) environmentally independent measures of disease severity, (3) measures of disease severity for species versus a sample of material tested in a greenhouse, (4) objective indicators of susceptible and non-susceptible species, (5) a means to objectively compare disease on targets versus nontargets. Of the 89 species evaluated by the MME, eight native N. American species were predicted to be susceptible. As a result of these predictions, these eight species were further evaluated to determine the amount of actual damage caused by CGS. This was done by comparing root and shoot areas and weights between non-inoculated plants and plants inoculated
Handling Editor: Kevin Heinz D. K. Berner (&) C. A. Cavin USDA, ARS, Foreign Disease-Weed Science Research Unit, Ft. Detrick, MD 21702-5023, USA e-mail:
[email protected]
with CGS. Results showed that several of the species exhibited some minor reduction in root weight and root area, but none of the species had any damage to above-ground plant parts. This supports the BLUP output in the initial host range determination tests. As a result of both analyses, there is no evidence that CGS would cause any non-target effects in nature. Keywords Ascomycota Colletotrichum gloeosporioides f. sp. salsolae Glomerella cingulata Russian thistle Salsola tragus Sordariomycetes Tumbleweed
Introduction To find and develop foreign plant pathogens for classical biological control of introduced invasive weeds in the US we discover diseases of the target weeds in their native range, isolate the responsible pathogens, determine if the pathogens are sufficiently damaging to be effective control agents, and determine if the pathogens are safe, i.e., are host specific, to release in N. America. Demonstration of a sufficiently narrow host range, restricted to the target weed, or at most to closely related non-native or noneconomically important plant species, is necessary before an agent will be approved by regulatory agencies for release into N. America. Selection of what non-target species to test has been based, for many years, almost universally on Wapshere’s
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centrifugal phylogenetic testing system (Wapshere 1974) in which both closely related taxa and unrelated taxa with morphological and biochemical similarities to the target weed are tested. Recently there have been calls to modernize this approach through the use of molecular phylogeny and the exclusion of testing unrelated taxa (Briese 2005). However, there are yet other problems in host range determination as conducted historically. In a definitive host range test, non-target plant species would, ideally, be evaluated for susceptibility to the biological control agent by comparing, in replicated tests, dry weights of inoculated and noninoculated plants to determine any damage attributable to the pathogen. However, when many different non-target species are to be evaluated, this approach is prohibitively time consuming and unnecessary. Since most non-target species would not be expected to be susceptible, unless the control agent is a poor choice, i.e., a generalist, a simpler system employing disease ratings on individual inoculated plants, in replicated tests, is the more efficient and frequently adequate approach. However, propagation material for many weedy species can be difficult to obtain and grow, and problems with the described approaches arise when there is inadequate material to test, or in the case of some threatened and endangered species, no material to test. Because candidate pathogens are exotic, all host-range tests in the USA must be done in a quarantine greenhouse. Greenhouse research conditions are artificially optimal for disease development in order to provide the most stringent tests of non-target species susceptibility. However, when a species exhibits a minor amount of disease there is substantial uncertainty whether this reflects a susceptible reaction or is an artifact of the inoculation methods and extremely favorable environment for disease development that results in an extension of the host range (Evans 2000) that is not predictive of the potential for disease in natural systems. In addition, most host range tests in these greenhouses involve small sample sizes that bring into question whether observed disease reactions are representative of the species as a whole or are peculiar only to the collection of plant material used in the test. Thus a central problem, in light of the issues raised, remains how to avoid discarding potentially beneficial organisms, for which a lot of research effort has been invested, while ensuring that the organisms are safe
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to release. What is needed is a system that can provide: (1) disease assessments for rare and difficult or impossible to grow species, (2) environmentally independent measures of disease severity or incidence, (3) measures of disease severity or incidence for species versus only an infinitesimal sample of material tested in a greenhouse, (4) objective indicators of susceptible and non-susceptible species, and (5) a means to objectively compare disease on targets versus non-targets. Host-range determinations based on disease reactions of the target weed, Russian thistle or tumbleweed, (Salsola tragus L., Family: Chenopodiaceae, subfamily: Salsoloideae, tribe: Salsoleae), and related non-target plants, were recently conducted (Berner 2010; Berner et al. 2009a, b). As there are no native N. American species within the tribe Salsolae, all native species are Old-World species (Akhani et al. 2007; Kadereit et al. 2003), S. tragus is a good target for biological control efforts in the USA. According to the USDA, ARS Systematic Mycology and Microbiology Laboratory (SMML) fungal databases, there are about 13 fungus species, not necessarily aggressive pathogens, reported from S. tragus and its synonyms in N. America and 30 species reported in the native range of the plant (Farr and Rossman 2011). Thus there are about 76.4% fewer fungus species in the naturalized versus native range of S. tragus. According to Mitchell and Power (2003) this difference is indicative of invasive weed species that have undergone enemy release when introduced to the naturalized range. In other words, S. tragus was likely introduced to N. America without the natural enemies that kept it in check in the native range, and this release from natural enemies has led to the invasiveness of S. tragus in N. America. The likelihood of enemy release, in turn, indicates that classical biological control of S. tragus, by introducing pathogens, or other natural enemies, on S. tragus from its native range, has potential to be a successful control strategy. To meet the five aforementioned requirements for an improved system of host-range determination, Berner et al. (2009a, b) combined ranks of disease severity ratings with genetic distance matrices, based on DNA sequences of the species being evaluated, and analyzed these data with Henderson’s mixed model equations (MME) (Henderson 1975, 1977) to generate best linear unbiased predictors (BLUPs) of
Finalizing host range determination of a weed biological control pathogen
the disease reactions for each species. This was done for two exotic pathogens of S. tragus which are from the native range of the weed (Farr and Rossman 2011). These pathogens were an obligate pathogenic rust fungus Uromyces salsolae Reichardt (Basidiomycota, Pucciniaceae) (Berner et al. 2009a) and a facultative pathogenic fungus Colletotrichum gloeosporioides (Penz.) Penz. & Sacc. in Penz. f. sp. salsolae (CGS, Ascomycota, Glomerellaceae; teleomorph Glomerella cingulata [Stoneman] Spauld. & H. Schrenk) (Berner et al. 2009b). Results indicated that of the 64 species analyzed for susceptibility to U. salsolae only non-native Salsola spp. were susceptible, based on significant non-zero BLUPs, and no further evaluation was necessary. However, of the 89 species analyzed for susceptibility to CGS, some native N. American species were predicted susceptible based on significant non-zero BLUPs. The objectives of the current study were, for these predicted susceptible species, to: (1) determine how well susceptibility predicted by BLUPs, based on ranks of disease ratings and a genetic distance matrix, relates to actual damage caused by the disease and (2) determine whether disease caused by CGS on these non-target species is damaging enough to preclude release of CGS for biological control of S. tragus in the USA.
Materials and methods Fungus culture and inoculation procedure Colletotrichum gloeosporioides f. sp. salsolae isolate 96-067 (BPI 878740, GenBank # EU805538), collected originally from a Salsola sp. in Hungary (Schwarczinger et al. 1998), was used in all tests. Cultures of CGS were grown in Petri dishes for two weeks on 20% V-8 Juice agar at room temperature (20°C) with daily 12 h dark-light cycles. Spore suspensions were made by gently washing the surface of the medium with distilled water and polysorbate 20 solution (two drops per 100 ml) and brushing suspended spores into a beaker with a camel hair brush. The spore concentration in this suspension was determined with a haemacytometer and adjusted to 1 9 106 spores ml-1. This spore suspension was applied to four-week-old plants with an atomizer until the foliage was completely wet. The plants were
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then placed in a 25°C dew chamber with no light. Pots of plants were removed from the dew chamber after 18 h and then placed in randomized positions on a bench in a greenhouse kept at 20°C with overhead irrigation and supplemental light. In the damage assessment study, pots of non-inoculated plants of the same age were included within the randomized array of test plants on the same greenhouse bench. Generation of BLUPs For the initial host-range determination tests, 89 plant species (92 accessions) related to S. tragus L., the target weed, were evaluated for susceptibility to CGS (Berner et al. 2009b). This was done by combining ranks of disease severity ratings with a relationship matrix derived from internal transcribed spacer DNA sequences and analyzing these data with MME to produce BLUPs for each species (Berner et al. 2009a, b). In repeated tests, plants of the test species were inoculated as described and rated for disease severity based on a scale from 0 to 4, where: 0 = no macroscopic symptoms; 1 = small or isolated lesions, \25% of the plant diseased; 2 = some coalesced lesions, 25–50% of the plant diseased; 3 = many coalesced lesions, [50% of the plant diseased; and 4 = severe disease, dead plant. Between one and ten plants were inoculated in each repetition for each species. Plants of S. tragus were included as a positive check in each repetition. Each repetition reflected a separate inoculation, and from two to ten repetitions were conducted for most species, depending on availability of plant material and relative importance of the species in specificity tests. Disease data for species for which there were no disease severity ratings were represented as missing values in the dataset. The disease severity ratings were ranked, using the Rank procedure of SAS (SAS Institute Inc. 2004) for each plant within each species and repetition. The rank data were then analyzed with the Mixed procedure of SAS, with species as a random effect, to generate the variance estimate for species. For each species evaluated, DNA sequences of the internal transcribed spacer 1 (ITS1), 5.8S ribosomal RNA (5.8S rRNA), and internal transcribed spacer 2 (ITS2) regions (ITS sequences) were either generated in our laboratory or obtained from GenBank at the National Center for Biotechnology Information (NCBI) in the USA. A genetic distance matrix
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among species was developed from the ITS sequences of the species. This was done by aligning the sequences with the ClustalW2 tool (Larkin et al. 2007) and generating a matrix of pairwise maximum likelihood distances from the aligned sequences with TREE-PUZZLE software (Schmidt et al. 2002). A separate file of maximum likelihood branch lengths was also generated by the quartet puzzling program, and the branch lengths from this file were read into TreeViewX software (Page 1996) to draw a cladogram of the species tested. The matrix of pairwise maximum likelihood distances was transformed into a relationship matrix by subtracting each element from 1, so that the relation of each species with itself was 1, and then multiplying each element by the variance among species obtained from the previously described statistical analysis. The resultant 92 9 92 matrix of variances and covariances along with the disease severity rank data were read into the Mixed procedure of SAS, according to Berner et al. (2009a, b) to generate BLUPs for each species, standard errors of the BLUPs, and t tests comparing each BLUP against zero. This procedure was used to generate BLUPs for 59 of the inoculated species and for an additional 33 species on the basis of ITS sequence data alone; i.e., these 33 species had no observed disease data. Non-target species with BLUP values significantly different from zero were considered potentially susceptible, and they were selected for more detailed evaluations. Damage assessment To evaluate damage caused by CGS on selected native non-target plant species, oven-dry shoot and root weights and surface areas, of the same shoots and roots, were compared between non-inoculated and inoculated treatments. Plant species tested were those native N. American species with significant non-zero BLUPs from the MME analyses of Berner et al. (2009b). Also tested were the target weed, S. tragus, and its relatives S. paulsenii, and S. australis, two species susceptible according to the BLUPs, and S. soda, a relative not susceptible according to the BLUP. Plants of each selected species were grown from seeds in 10-cm-diameter pots in a quarantine greenhouse. To enable timely processing of roots, i.e., thorough washing to remove all soil particles, and to allow for inoculation of
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different species at the same physiological growth stage, inoculations were staggered. Different plant species were included at each of five inoculation times, but Salsola tragus plants were included in each inoculation to ensure, through disease monitoring, that each inoculation was successful in producing disease on the target species. For most species, ten experimental plants were inoculated and another ten plants of each species were not inoculated. However, only four plants of Sarcocornia utahensis and ten plants of Salsola australis were available to inoculate, with another four and seven plants, respectively, left not inoculated. Nitrophila mohavensis plants, from rooted cuttings of uniform size, were substituted for N. occidentalis, and tested as described. Disease ratings were based on a scale from 0 to 10, where: 0 = no observable symptoms, 1 = 1–10% of the plant diseased, 2 = 11–20% of the plant diseased, etc., and 10 = 91–100% of the plant diseased. Ratings were taken weekly for four weeks post-inoculation. Rankings of disease ratings at four weeks post-inoculation, for each inoculation time, were statistically analyzed. After the last disease rating, above-ground shoots were cut off at soil level, scanned with a Canon LiDE 500F scanner, and placed in glassine bags for drying. Root sections of these plants were carefully washed, scanned and prepared as described for the shoots. After 48 h of drying at 100°C, shoots and roots were weighed. Stored images from the scanner were analyzed, to get a two-dimensional estimate of surface areas, with Assess 2.0 Image Analysis Software for Plant Disease Quantification, Version 2.0, Copyright 2002–2008 American Phytopathological Society. Root and shoot weights and surface areas for noninoculated and inoculated plants, and disease rankings for inoculated plants, were analyzed with the Mixed procedure of SAS. The experimental design was a randomized partially balanced incomplete block with inoculation times as blocks. The experimental unit was plant (= replication) in each inoculation treatment (inoculated or non-inoculated) and inoculation time. The variables root and shoot weights and surface areas were analyzed with species, inoculation treatment, and the interaction as fixed effects and inoculation time as a random effect. Estimate statements were written to generate BLUPs, standard errors, and Pr [ |t| values for the difference between inoculated and non-inoculated treatments
Finalizing host range determination of a weed biological control pathogen
for each species and for comparison of these differences with the differences for S. tragus. The BLUPs of these treatment differences for each species were plotted with the G3D procedure of SAS to generate three-dimensional plots of root and shoot weight versus root area and shoot area. Ranks of disease ratings were analyzed with species and inoculation time as random effects to generate BLUPs, standard errors, and Pr [ |t| values for species. A genetic relationship matrix was not, in this case, integrated into the analysis of disease rankings.
Results Ten native or commercially important plant species that were evaluated by Berner et al. (2009b) were predicted susceptible, i.e., had significant (P B 0.05) non-zero BLUPs. These are listed in Table 1 and indicated in bold text in Fig. 1. These ten species were widely separated in genetic relatedness, in contrast to the susceptible Salsola species, which were closely related (Fig. 1). In this test there was only ITS sequence data and no observed disease data for Sarcocornia utahensis, Bassia americana, Suaeda calceoliformis, and Suaeda occidentalis. No seeds of Suaeda occidentalis or Nitrophila occidentalis could be obtained for damage assessment testing, but the PLANTS database (USDA NRCS 2008) regards S. occidentalis a synonym of S. calceoliformis. These two species clustered together (Fig. 1) and had similar BLUPs, generated without observed disease severity data (Table 1). Spinacia oleracea was the only commercially important species with a non-zero BLUP. However, prior extensive testing of this species indicated that disease is correlated with plant senescence and that non-senescent plants are not susceptible (Berner et al. 2009b). Spinach therefore was not evaluated in this study for damage caused by CGS. Best linear unbiased predictors of disease severity rankings for test species that were inoculated in this study with CGS are presented in Table 2. Several differences with the BLUPs in Table 1 were found. Sarcocornia utahensis, Suaeda calceoliformis, and Salsola australis did not become diseased by CGS (Table 2) despite prediction of susceptibility in the absence of inoculations (Table 1). For the other species, BLUPs that were significant in Table 1 were
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also significant in Table 2, although Bassia americana had no observed disease data for the BLUP in Table 1. Least squares means of differences in root weight, root area, shoot weight, and shoot area between noninoculated plants and plants inoculated with CGS are presented in Table 3. For all of the variables, inoculated plants of S. tragus weighed less and had smaller image area than non-inoculated plants, and these differences were highly significantly (P B 0.01). This was only true for the target weed, S. tragus, and the differences between S. tragus and the other species were highly significant for all variables. As a visual gauge of the amount of damage done by CGS to S. tragus, comparison photos of inoculated and non-inoculated S. tragus plants are presented in Fig. 2. Graphs of the least squares means of the differences in Figs. 3 and 4 show that S. tragus is uniquely susceptible to CGS among the species tested. For both root (Fig. 3) and shoot (Fig. 4) weights versus root and shoot areas, all other species were clustered in a diametrically opposed fashion to S. tragus. Of these species, roots of inoculated plants weighed significantly less than non-inoculated plants only for Bassia americana and Suaeda calceoliformis, and these differences were about 28% and 58%, respectively, of the difference for S. tragus. There were no observable disease lesions on the roots of these plants. Roots of inoculated plants of Salicornia bigelovii weighed significantly more than roots from non-inoculated plants. Root and shoot areas and shoot weight were also greater, although not significantly, for inoculated plants of S. bigelovii and Sarcocornia utahensis. Root weights of the latter were also greater for inoculated plants. Despite the lack of disease lesions on the roots, root areas for B. americana, S. calceoliformis and S. moquinii were also significantly less than non-inoculated plants but were only about 23–26% of the difference for S. tragus. Differences in shoot areas and shoot weights were not significantly different from zero for any species other than S. tragus and S. paulsenii. Differences in shoot area and shoot weight were not significant for the other Salsola spp., S. australis or S. soda, and root area and weight were not affected for any Salsola spp. other than S. tragus. CGS could not be re-isolated from roots or shoots because they had been oven-dried for sampling and the fungus was likely killed as a result.
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Table 1 Mixed model predictors (BLUPs) of disease reaction of plant species to Colletotrichum gloeosporioides f. sp. salsolae Genus speciesa
Mixed model predictors BLUPb
Standard error of predictionc
Pr [ |t|d
Salsola kali—UK
247.92
10.23
\0.0001
Salsola tragus
246.73
9.84
\0.0001
Salsola collina
235.40
70.70
\0.0001
Salsola paulsenii
225.51
7.59
\0.0001
Salsola kali—Akhani
224.75
7.93
\0.0001
Salicornia bigelovii
213.39
14.95
\0.0001
Salsola australis
208.14
10.29
\0.0001
Salsola kali—Maui
207.53
10.58
0.0001
Salicornia maritima
205.02
14.86
0.0002
Sarcocornia utahensis
196.41
20.63
0.0015
Sarcocornia fruticosa
190.04
21.67
0.0027
Bassia hyssopifolia
188.26
17.62
0.0026
Bassia scoparia
187.80
9.01
0.0036
Nitrophila occidentalis
184.10
16.80
0.0070
Halothamnus subaphyllus Arthrocnemum glaucum
176.36 176.08
18.05 19.17
0.0152 0.0091
Bassia americana
176.11
24.97
0.0120
Bassia prostrata
172.30
20.92
0.0150
Suaeda calceoliformis
169.86
28.41
0.0269
Kalidium foliatum
169.85
22.65
0.0159
Spinacia oleracea
167.73
14.70
0.0104
Suaeda glauca
166.54
25.34
0.0261
Polycnemum majus
165.83
26.21
0.0478
Suaeda occidentalis
165.42
27.66
0.0361
Suaeda moquinii
165.27
14.03
0.0119
Suaeda taxifolia
164.68
13.89
0.0124
Suaeda maritima
162.11
25.61
0.0399
Halocnemum strobilaceum
159.38
20.36
0.0259
Suaeda vera
158.36
25.13
0.0510
Halogeton glomeratus Salsola soda
153.59 145.83
16.78 17.62
0.0389 NSe
Salsola orientalis
144.60
17.65
NS
Salicornia virginica
137.25
13.30
NS
Suaeda californica
129.49
15.80
NS
Nitrophila mohavensis
104.73
33.12
NS
The list is a subset of 92 accessions evaluated with the MME in Berner et al. 2009b. Species in bold type are either native or species of economic importance in N. America a
Species are arranged in order of descending BLUP values
b
BLUP includes fixed intercept estimate
c
Standard error of prediction based on BLUP of random species effect plus intercept
d
Pr [ |t| based on BLUP of random species effect without intercept
e
Not significantly different from zero at P B 0.05
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Fig. 1 Quartet puzzling tree from analysis of ITS sequence data. Numbers above the branches are quartet puzzling values indicating percent support for the internal branches of the tree. Native or commercially important species with significant non-zero BLUPs are indicated in bold text
Discussion In addition to being able to generate predictions for species with no observed disease reaction data, two other important properties of BLUPs generated from the MME are that they are more conservative, i.e., predict more susceptible species, and safer, i.e., have lower probability of erroneously deeming a species not susceptible, than other evaluation methods (Berner 2010). These properties are born out in the current study where the species Sarcocornia utahensis, Salsola australis, and Suaeda calceoliformis (and, by synonymy, S. occidentalis), with significant BLUPs for ranks of disease severity ratings in Table 1, were found to have non-significant BLUPs when not combined with a genetic relationship matrix
(Table 2). This is not surprising for S. utahensis and S. calceoliformis, since the BLUPs in Table 1 were generated without observed disease data. Salsola australis was found to have a significant non-zero BLUP in the initial tests (Table 1), but actual disease ratings for this species were quite low and averaged 0.57, on a 0–4 scale (data not shown). This is also consistent with the findings of Bruckart et al. 2004. Because S. australis is closely related to S. tragus (Fig. 1), and was formerly identified as Salsola tragus ‘‘Type B’’ (Bruckart et al. 2004, Hrusa and Gaskin 2008), the genetic relationship matrix and the MME undoubtedly ‘‘pulled’’ the BLUP toward the S. tragus type of reaction. Disease reactions, based on BLUPs and root and shoot dry weights and surface areas indicated that the order of susceptibility
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Table 2 BLUPs from mixed model analysis of ranks of disease ratings, based on a 0–10 scale where 0 = no disease and 10 = 91–100% diseased tissue, of plants inoculated with CGS and evaluated four weeks after inoculation Species
BLUPS of ranks of disease rating Estimate
Bassia americana
SE
32.6* (6.5)
5.39
15.8 (1.1)
4.51
Salicornia bigelovii
19.1* (5.1)
4.52
Salicornia maritima
28.1* (9.8)
4.42
8.1 (0.3)
4.94
Salsola australis
8.8 (0.3)
4.41
Salsola paulsenii
32.0* (10.0)
4.41
5.1 (0.0)
4.41
Nitrophila mohavensis
Sarcocornia utahensis
Salsola soda Salsola tragus
24.2* (7.5)
3.87
1.6 (0.0)
5.39
24.9* (3.4) 28.9* (4.7)
5.39 5.39
Suaeda calceoliformis Suaeda moquinii Suaeda taxifolia Estimates of average disease ratings are in parentheses * Indicates significant difference from zero at P B 0.05
Table 3 Least squares means of differences in root weight, root area, shoot weight, and shoot area between plants not inoculated and inoculated with CGS Species
Root weight (g)
Root area (cm2)
Shoot weight (g)
Shoot area (cm2)
Estimate
Estimate
Estimate
Estimate
SE
SE
SE
SE
Bassia americana
0.149*
0.0750
12.87*
6.470
0.265
0.1661
14.37
9.934
Nitrophila mohavensis
0.056
0.0559
4.86
4.822
0.043
0.1238
5.38
7.404
Salicornia bigelovii
-0.187*
0.0759
-11.38
6.543
-0.300
0.1680
-16.61
10.045
Salicornia maritima
0.037
0.0750
4.37
6.470
0.155
0.1661
9.38
9.934
-0.097
0.1187
-5.27
10.229
-0.054
0.2626
-2.25
15.707
Salsola australis
0.010
0.0827
-6.59
7.129
-0.019
0.1830
0.82
10.947
Salsola paulsenii
0.032
0.0750
4.12
6.470
0.420**
0.1661
34.24**
9.934
Salsola soda
0.054
0.0750
4.42
6.470
0.209
0.1661
15.10
9.934
Salsola tragus Suaeda calceoliformis
0.526** 0.304**
0.0407 0.0750
55.17** 14.33*
3.511 6.470
1.180** 0.119
0.0901 0.1661
93.56** 9.47
5.392 9.934
Suaeda moquinii
0.092
0.0750
14.37*
6.470
0.232
0.1661
15.79
Suaeda taxifolia
-0.011
0.0750
0.70
6.470
0.030
0.1661
Sarcocornia utahensis
0.002
9.934 9.934
Positive values indicate greater weights or larger areas for the not inoculated plants while negative values indicate the opposite * Indicates significant difference from zero at P B 0.05 ** Indicates significant difference from zero at P B 0.01
to CGS among the S. tragus complex in California (Hrusa and Gaskin 2008) was, from most to least susceptible: S. tragus [ S. paulsenii [ S. australis = S. ryani. S. ryani, formerly S. tragus ‘‘Type C’’, is the allohexaploid hybrid between S. tragus and S. australis (Hrusa and Gaskin 2008). Data for the
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disease reactions of S. ryani were not presented because this species was not included in the MME analysis, that included the genetic relationship matrix, and because the disease reaction based on the other variables was essentially the same as S. australis.
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Fig. 2 Scanned images of the shoots of Salsola tragus plants not inoculated (control) and inoculated with CGS. Weights and surface areas are indicated in the insets Fig. 3 Least squares mean differences in root weight, root area, and shoot area between non-inoculated plants and plants inoculated with CGS
Although BLUPs were more conservative in predicting susceptibility of S. utahensis, S. australis, and S. calceoliformis, the BLUP for Bassia americana, for which there was no observed disease data, in Table 1 was an accurate predictor of significant disease severity in Table 2. Thus when a BLUP is not significant and statistically equal to zero, there is a very high probability that the species is not susceptible. However, because genetic relationships are
included in the analysis, there may be some false positive predictions associated with related species. These can then be verified in additional tests, as demonstrated in this study. Furthermore, those species found not susceptible, i.e., with non-significant BLUPs for disease severity ranking, in Table 2 were not damaged by CGS and that less susceptible species, i.e., those with non-significant BLUPs in Table 1, would not likely be damaged by CGS either.
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D. K. Berner, C. A. Cavin
Fig. 4 Least squares mean differences in shoot weight, root area, and shoot area between non-inoculated plants and plants inoculated with CGS
Significant disease severity on B. americana was also reflected in some minor negative effects on root weight and root area although these were significantly less than for S. tragus. This was also true for root area of Suaeda moquinii but not for S. taxifolia, both of which had significant non-zero BLUPs for disease severity ranking in both Tables 1 and 2. Although BLUPs did not accurately predict significant disease severity ranking for Suaeda calceoliformis, they did accurately predict some negative effects of CGS on root weight and root area of this species. These effects were minor relative to S. tragus, and there was no damage to above-ground plant parts for any of these species. In fact, S. bigelovii responded positively to inoculation with CGS with significantly increased root weight. Nitrophila mohavensis did not have significant BLUPs in either Tables 1 or 2 and did not have any significant differences, for any variable, between non-inoculated and inoculated plants, but this species was substituted for N. occidentalis which was predicted susceptible in Table 1. Although no seeds or planting material could be obtained, in this study, for N. occidentalis, further attempts to obtain these materials and test this species need to be made. However, given the most distant relationship of any species in Table 2 with S. tragus (Fig. 1), it is not likely
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that N. occidentalis would exhibit any more damage than the more closely related species that were tested. In terms of the objectives of the study, susceptibility predicted by BLUPs, based on ranks of disease ratings and a genetic distance matrix, did not relate well to the lack of actual damage caused by the disease on the eight native plant species that were tested. This is undoubtedly due to the conservative and safe properties of BLUPs which serve as excellent precautionary principles, although more species may be predicted susceptible than those that actually are. None of the eight native species were damaged by CGS, i.e., had significant differences between non-inoculated and inoculated plants on above-ground plant parts, although there were some minor effects on the roots of a couple of species. Thus there is no evidence to warrant preclusion of release of CGS for biological control of S. tragus in the USA. There are reported to be 39 species in the genus Colletotrichum (Sutton 1992). Teleomorphs of these species, when present, are in the genus Glomerella (Sutton 1992). For both the anamorph and teleomorph species, both botanical varieties and formae speciales have been reported (Sutton 1992). Both of these designations are indicative of intra-specific host
Finalizing host range determination of a weed biological control pathogen
specificity. Thus, among these 39 species, there is considerable variability in pathogenicity, i.e., the ability to cause disease on any given plant species. Although host plant interactions among these species have been classified according to symbiotic relationships based on commensulism, mutalism, or parasitism (Rodriguez and Redman 2000), symbiotic relationships within C. gloeosporioides have never been confirmed to be other than parasitic, although C. gloeosporioides, and other Colletotrichum spp. can also grow as facultative saprophytes/parasites on dead plant material and artificial media (Templeton et al. 1984). This facultative saprophytic/parasitic character has been a concern, albeit unwarranted, to some regulators of biological control agents, since the fungus can theoretically survive in nature without a host and, conceivably, cause disease on other plants at some unspecified time in the future. However, the ability of C. gloeosporioides to grow on a variety of dead and artificial substrates in no way relates to the ability of the fungus to cause disease on any living plant species. In fact, Colletotrichum gloeosporioides is, perhaps, the most widely and safely used plant pathogen for biological control of weeds, and there are a number of extremely host-specific special forms (formae speciales) that cause disease on only one host plant. A commercial mycoherbicide, LockDown (formerly Collego) with C. gloeosporioides f. sp. aeschynomene as the active ingredient, is currently being produced and marketed by Natural Industries, Inc., for control of northern jointvetch (Aeschynomene virginica (L.) Britton et al.) in rice in the southern USA. This product, by one name or another, has been used to control this weed in rice since the early 1980s (Templeton et al. 1984; TeBeest 1988) without any non-target effects in nature. A number of other formae speciales of C. gloeosporioides have also been successfully used for biological control of weeds, and research has shown that these formae speciales are also quite host specific and not damaging to non-target species. Some of the target weeds controlled by these formae speciales include: Miconia calvescens (Killgore et al. 1999), Malva pusilla and Abutilon theophrasti (Mortensen 1988; Mortensen and Makowski 1997), Clidemia hirta (Trujillo et al. 1986), Jussiae decurrens (Boyette et al. 1979), and Cuscuta spp. (Cartwright and Templeton 1989). Thus there is considerable precedent for effective
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and safe formae speciales of C. gloeosporioides for biological control of weeds. As a result of this study, CGS has now been demonstrated to be another effective and safe formae speciales for biological control of S. tragus. In conclusion, analysis of CGS disease severity rankings by the MME reduced the number of species needing further evaluation from 89 species (92 accessions) to eight native N. American species. The MME and BLUPs also satisfied the five desired requirements of an improved system of host-range evaluation as outlined in the introduction. Through a more intensive subsequent assessment of actual damage caused by CGS to the eight native species, no damage to above-ground plant parts was found for any of the species. Thus there is no evidence that non-target species would be harmed by CGS in nature.
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Author Biographies Dana K. Berner is currently evaluating Bromus tectorum, Carduus spp., Centaurea solstitialis, Cirsium arvense, Crupina vulgaris, Persicaria perfoliata, Rhaponticum repens, Salsola tragus, Taeniatherum caput-medusae, and Vincetoxicum spp. as targets for classical biological control with plant pathogens. FDWSRU has previously released three plant pathogens for classical biological control of invasive weeds in the USA, and another petition for release is pending. This research is part of host-range determinations of exotic plant pathogens for classical biological control of invasive weeds with plant pathogens under the weed biological control project (led by Dr. Dana Berner) at the Foreign Disease-Weed Science Research Unit (FDWSRU) of USDA, ARS at Ft. Detrick, Maryland, USA. Craig A. Cavin is currently evaluating Bromus tectorum, Carduus spp., Centaurea solstitialis, Cirsium arvense, Crupina vulgaris, Persicaria perfoliata, Rhaponticum repens, Salsola tragus, Taeniatherum caput-medusae, and Vincetoxicum spp. as targets for classical biological control with plant pathogens. FDWSRU has previously released three plant pathogens for classical biological control of invasive weeds in the USA, and another petition for release is pending.
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