Genetic Variation of Growth Traits and Genotype-by-Environment Interactions in Clones of Catalpa bungei and Catalpa fargesii f. duclouxii

Clones of Catalpa bungei and Catalpa fargesii f. duclouxii were studied over several years in central China to explore genetic variation in growth traits and to identify clones of high wood yield and high stability. The genetic parameters for height, diameter at breast height (DBH), and stem volume of clones, were estimated. The effect of clone × year on the increment of stem volume in the two species was analyzed by genotype and genotype × environment (GGE) biplot methods. Significant differences in growth traits among clones and between species were found. The growth of C. bungei exceeded that of C. fargesii f. duclouxii after 4 years. Furthermore, from the 5th year, the repeatability and genetic variation coefficient (GCV) of the C. bungei clones were higher than those of the C. fargesii f. duclouxii clones in most cases. The phenotypic variation coefficient (PCV) of the C. fargesii f. duclouxii clones was significantly lower than that of the C. bungei clones. The repeatability of stem volume was intermediate or high in the two species. ANOVA revealed significant effects of the clone by year interaction in these two species. GGE biplot analysis revealed that wood yield and stability were largely independent in C. bungei; clones 22-03, 19-27, and 20-01 were the optimal clones in this species. In contrast, the optimal clones 63 and 128 of C. fargesii f. duclouxii combined the desired characteristics of high yield and high stability. In conclusion, our results indicated that the height and stem volume of C. bungei was under strong genetic control, whereas that of C. fargesii f. duclouxii was influenced by the environment more than by genetic effects. Genetic improvement by clone selection can be expected to be effective, as the repeatability of stem volume was high. Francis and Kannenberg’s method and GGE biplot analysis were used in combination to evaluate the clones. C. bungei clone 22-03 and C. fargesii f. duclouxii clones 63 and 128 were identified as the optimal clones, which exhibited both a high increment of stem volume and high stability.


Introduction
Manchurian catalpa (Catalpa bungei) and Catalpa fargesii f. duclouxii belong to the Catalpa genus of the Bignoniaceae family and are native to China. C. bungei is mainly distributed in the Yellow River and Yangtze River regions. C. fargesii f. duclouxii is distributed within the Yunnan-Guizhou plateau. They are recognized for their straight stems and high quality timber, which is of high density and has high bending strength and hardness. These characteristics make them valuable material for furniture production [1,2]. However, their natural germplasm resources are becoming scarce due to hercogamy and deforestation [3]. Thus, the selection of fast-growing varieties is urgently needed to alleviate the shortage of Catalpa wood.
Tree breeding is the application of genetic, reproductive biology and economics principles to the genetic improvement and management of forest trees. Significant genetic variations among families or clones suggest a strong foundation for genetic improvement of Catalpa trees [4,5]. Clonal forestry has become increasingly important for forestry development [6][7][8][9]. In breeding work, the heritability of a target trait refers to the degree of variation in a phenotypic trait in a population that is due to genetic variation among individuals in that population [10]. Because clones of a single individual have the same genotype, we cannot estimate heritability. However, repeatability can be estimated. Repeatability is a measure of the stability of a trait expressed in a fluctuating environment. The higher the heritability or repeatability is, the greater the genetic control of the trait and the lower the influences of environmental effects [11]. Furthermore, the genetic gain of a selected population can be estimated by heritability or repeatability. Genetic gain can be improved more rapidly with appropriate genetic testing and selection of clones than of families or provenances. However, phenotypic variation arises from variation in individual genetic background and environmental effects [12]. Clones can have stronger genotype-by-environment interactions (GEIs) than families or provenances as a result of their specific genotypes [13]. Environmental effects can be divided into site and year effects. Environmental factors such as temperature, rainfall, atmospheric conditions, soil conditions and biotic factors vary among different sites and among years within sites. For perennial species, year effects should be seriously considered.
The systematic study of GEIs can reduce risk in variety selection and improve production [14,15]. Previously, regression coefficients were frequently used to study GEIs and evaluate trait stability [16,17]. However, this method ignores genetic effects among species and clones. The genotype and genotype × environment (GGE) model overcomes this defect by considering the effects of both genotype and genotype × environment. To date, GGE has been widely used to evaluate the growth stability in crop yield [18][19][20]. However, as the majority of crops are therophytes or biennials, GEI studies of crops mostly focused on site effects. Trees are perennials, and a year represents one growth cycle of a tree. To enhance genetic improvement and maximize clone potential, it is important to analyze the stability of plant growth over years. In our study, clones of C. bungei and C. fargesii f. duclouxii were investigated, and several years of data on clone growth were collected (1) to estimate and compare genetic parameters of growth traits in clones and evaluate the variation in growth traits, (2) to evaluate the stability of clone stem volume across years, and (3) to identify clones with high and stable yield as optimal clones.

Site and Materials
Ramets of 32 clones of C. bungei and 20 clones of C. fargesii f. duclouxii were planted in Laodong Village of Henan Province (32. Table 1. A randomized block design was applied, with 2 ramets in each clone plot and 5 replications. The height and DBH (diameter at breast height) of the clones were measured at the end of each yearfrom 2009 to 2014.Information on the distribution of materials is provided in Figure 1. elevation is 145 m, and the soil of the experimental field is yellow brown loam and has high natural fertility.

Data Analysis
Variation and the genetic parameters (repeatability, clonal variance) were estimated of growth traits among clones for C. bungei and C. fargesii f. duclouxii were analyzed. ASReml-R 3.0 [21] and SAS 9.4 [22] software was used to perform ANOVA, F-tests and evaluation of genetic parameters.

Analysis at a Species Level for Each Year
A multifactor linear model was followed for each individual trait per year: where yijkl is the observed value of clone j in species i in block k; is the mean value of the population; is the fixed effect of species i = 1, 2; ( ) is the fixed effect of clone j within species i, j = 1, 2, …, 20 for C. fargesii f. duclouxii, j = 1, 2, …, 32 for C. bungei; is the fixed effect of block k = 1, …, 5; ( ) is the fixed effect of the interaction of species i and block k; and is the random error, NID (Normally and independently distributed) (0, ). The experimental field was in a region with a humid and subhumid continental monsoon climate. The mean annual temperature ranges from 14.4 • C to 15.7 • C, the mean annual precipitation ranges from 703.6 mm to 1173.4 mm, and the annual frost-free period is 220 days to 245 days. The elevation is 145 m, and the soil of the experimental field is yellow brown loam and has high natural fertility.

Data Analysis
Variation and the genetic parameters (repeatability, clonal variance) were estimated of growth traits among clones for C. bungei and C. fargesii f. duclouxii were analyzed. ASReml-R 3.0 [21] and SAS 9.4 [22] software was used to perform ANOVA, F-tests and evaluation of genetic parameters.

Analysis at a Species Level for Each Year
A multifactor linear model was followed for each individual trait per year: where y ijkl is the observed value of clone j in species i in block k; µ is the mean value of the population; S i is the fixed effect of species i = 1, 2; C(S) ij is the fixed effect of clone j within species i, j = 1, 2, . . . , 20 for C. fargesii f. duclouxii, j = 1, 2, . . . , 32 for C. bungei; B k is the fixed effect of block k = 1, . . . , 5; (SB) ik is the fixed effect of the interaction of species i and block k; and e ijkl is the random error, NID (Normally and independently distributed) (0, σ 2 e ).

Analysis at a Clonal Level for Each Individual Year
An ANOVA to evaluate the clone effect in each species and year was carried out using the following model: where y ijk is the observed value of clone i in block j; µ is the mean value of the population; C i is the random effect of clone i = 1, 2, . . . , 20 for C. fargesii f. duclouxii, i = 1, 2, . . . , 32 for C. bungei, NID(0, σ 2 C ); B j is the fixed effect of block j = 1, 2, . . . , 5; and e ijk is the random error, NID(0, σ 2 e ). The formula of repeatability within years was as follows: where R is repeatability; σ 2 C and σ 2 e are the estimates of between-clone and within-clone variance, respectively, as obtained from the analysis of variance; and B is the number of blocks.
The formula of phenotypic variation coefficient was as follows: where σ is the standard deviation of the phenotypic variation, and X is the trait mean. The formula of genetic variation coefficient is expressed as follows: where σ 2 C is the clonal variance, and X is the trait mean. The genetic variation was estimated by Equation (2).

Analysis at a Clonal Level across Years
A second multifactor linear model was followed for each trait across years: where y ijkl is the observed value of clone j in year i in block k; µ is the mean value of the population; Y i is the effect of year i, NID(0, σ 2 Y ); C j is the effect of clone j, NID(0, σ 2 C ); B k is the effect of block k; (YC) ij is the effect of the interaction of year i and clone j, NID(0, σ 2 YC ); (YB) ik is the effect of the interaction of year i and block k, NID(0, σ 2 B ); (CB) jk is the effect of the interaction of clone j and block k; e ijkl is the random error. B k was treated as a fixed effect, and Y i , C j , (YC) ij , (YB) ik and (CB) jk were random effects, NID(0, σ 2 e ). In this model, year and block were 6 and 5, respectively, and the number of clones for C. bungei and C. fargesii f. duclouxii were 32 and 20, respectively.
The formula of repeatability across years was as follows: where R is repeatability; σ 2 C is the clone variance; σ 2 BC is the interaction of block and clone variance; σ 2 YC is the interaction of year and clone variance; σ 2 e is the environmental variance; and B is the number of blocks. The parameters were estimated using Equation (1). N, Y and C were the number of individuals, years and clones; MS: mean square; F: F statistic To interpret genotype × environment, a GGE biplot model was used and performed by R software 3.5.1 [23]. GGE biplots were constructed from the first two principal components (PC1 and PC2) derived by subjecting the environment-centered increment of stem volume means to singular-value decomposition. In this study, the weather conditions of different years were considered the environmental effect. The equation was as follows: where Y ij is the mean stem volume increment of clone i in year j; Y j is the mean stem volume increment of all clones in year j; λ 1 and λ 2 are the singular value decomposition for PC1 and PC2. ξ i1 and ξ i2 are the eigenvector of PC1 and PC2, respectively, for genotype i. η j1 and η j2 are the eigenvector of PC1 and PC2, respectively, for year j. ε ij is the random error. The formula of genetic gain was as follows: where R is repeatability; S is the selection differential; and X is the population mean.

Growth Differences between the Two Species in Different Years
The ANOVA results showed that the height of C. fargesii f. duclouxii was significantly greater than that of C. bungei in 2009 (Table 2 and Figure 2). However, in the fourth year, the height of C. bungei was consistently higher than that of C. fargesii f. duclouxii (Figure 2a). Stem volume showed patterns similar to that of height ( Figure 2c). From 2009 to 2011, the DBH of C. fargesii f. duclouxii was significantly higher than that of C. bungei. However, after 2012, the DBH of C. bungei exceeded that of C. fargesii f. duclouxii. This latter difference is likely the result of a genetic effect: C. bungei adapted more readily to the environment, as it is native to the Yellow River region.

Repeatability of Height, DBH and Stem Volume in the Two Species
The variance analysis of clones growth traits in different years was performed (Tables S1 and S2) It showed that most traits in 2009-2014 of two species were significantly different at the 0.05 or 0.01 level among clones. And the repeatability of traits was eatimated. The repeatability of height was consistently higher in C. bungei than in C. fargesii f. duclouxii (Figure 3a). The range of DBH repeatability in C. fargesii f. duclouxii was 0.65 to 0.72, which indicated a strong genetic effect on DBH in these clones ( Figure 3b). The repeatability of DBH in C. bungei was stable from 2010 to 2014 ( Figure  3b). The trends of repeatability in stem volume were largely identical between the two species: repeatability increased sharply from 2009 to 2010 and then remained largely stable. The repeatability of most of the traits in 2009 was very low. These might reflect the unstable statement of the plantlet, which was still taking root.

Repeatability of Height, DBH and Stem Volume in the Two Species
The variance analysis of clones growth traits in different years was performed (Tables S1 and S2) It showed that most traits in 2009-2014 of two species were significantly different at the 0.05 or 0.01 level among clones. And the repeatability of traits was eatimated. The repeatability of height was consistently higher in C. bungei than in C. fargesii f. duclouxii (Figure 3a). The range of DBH repeatability in C. fargesii f. duclouxii was 0.65 to 0.72, which indicated a strong genetic effect on DBH in these clones ( Figure 3b). The repeatability of DBH in C. bungei was stable from 2010 to 2014 (Figure 3b). The trends of repeatability in stem volume were largely identical between the two species: repeatability increased sharply from 2009 to 2010 and then remained largely stable. The repeatability of most of the traits in 2009 was very low. These might reflect the unstable statement of the plantlet, which was still taking root.

Variation Coefficients of Height, DBH and Stem Volume in the Two Species
The phenotypic variation coefficient (PCV) indicates the total degree of variation. The PCV of height was only approximately 10% for both species. The PCV of height in C. fargesii f. duclouxii increased in 2013 and 2014, whereas that in C. bungei decreased in 2013 and 2014 ( Figure 4a). Similar patterns were observed for the PCVs of DBH and stem volume (Figure 4b,c). These results indicated that the environmental responses of the two species changed in 2012. In addition, the PCV of stem volume in C. bungei and C. fargesii f. duclouxii ranged from 27.95%-36.50% and 26.48%-40.95%, respectively. The average PCV of stem volume was over 30% in both species. This result suggested there was abundant genetic variation, representing a strong foundation for improvement in stem volume in the two species.
The genetic variation coefficient (GCV) indicates the degree of variation due to genetic effects. The patterns of GCV for all traits were similar to those of repeatability. The GCV of height in C. fargesii f. duclouxii decreased continuously from the third year while the PCV of height in this species continuously increased (Figure 4a). These findings implied the environmental effect became more significant with increasing year in C. fargesii f. duclouxii. The GCVs of DBH and stem volume in C. fargesii f. duclouxii were approximately stable, but the PCVs of these two parameters continuously increased (Figure 4b,c). These data further suggested that the environmental effect played a leading role in the growth variation of C. fargesii f. duclouxii. In contrast, for C. bungei, the PCVs of height, DBH and stem volume continuously decreased from 2012, whereas the GCVs of DBH and stem volume remained largely stable (Figure 4b,c). These results suggested that the growth of C. bungei was under stronger genetic control than was that of C. fargesii f. duclouxii and that C. bungei exhibited stronger environmental adaptation than did C. fargesii f. duclouxii.

Variation Coefficients of Height, DBH and Stem Volume in the Two Species
The phenotypic variation coefficient (PCV) indicates the total degree of variation. The PCV of height was only approximately 10% for both species. The PCV of height in C. fargesii f. duclouxii increased in 2013 and 2014, whereas that in C. bungei decreased in 2013 and 2014 (Figure 4a). Similar patterns were observed for the PCVs of DBH and stem volume (Figure 4b,c). These results indicated that the environmental responses of the two species changed in 2012. In addition, the PCV of stem volume in C. bungei and C. fargesii f. duclouxii ranged from 27.95%-36.50% and 26.48%-40.95%, respectively. The average PCV of stem volume was over 30% in both species. This result suggested there was abundant genetic variation, representing a strong foundation for improvement in stem volume in the two species.
The genetic variation coefficient (GCV) indicates the degree of variation due to genetic effects. The patterns of GCV for all traits were similar to those of repeatability. The GCV of height in C. fargesii f. duclouxii decreased continuously from the third year while the PCV of height in this species continuously increased (Figure 4a). These findings implied the environmental effect became more significant with increasing year in C. fargesii f. duclouxii. The GCVs of DBH and stem volume in C. fargesii f. duclouxii were approximately stable, but the PCVs of these two parameters continuously increased (Figure 4b,c). These data further suggested that the environmental effect played a leading role in the growth variation of C. fargesii f. duclouxii. In contrast, for C. bungei, the PCVs of height, DBH and stem volume continuously decreased from 2012, whereas the GCVs of DBH and stem volume remained largely stable (Figure 4b,c). These results suggested that the growth of C. bungei was under stronger genetic control than was that of C. fargesii f. duclouxii and that C. bungei exhibited stronger environmental adaptation than did C. fargesii f. duclouxii.

Analyses of Growth Traits in the Two Species
The ANOVA showed that the height, DBH and stem volume of the two species were significantly different at the 0.01 level among clones and blocks and that year × clone had a significant effect at the 0.01 level on all these traits except height in C. fargesii f. duclouxii, where the interaction effect was significant at the 0.05 level (Table 3). These findings indicated that (1) the clones of the two species showed significant variation, which indicated the selection of clones could be performed with high reliability, and (2) GEIs were significant in the two species. Thus, an assessment of the stability of clone growth was necessary.
The variance components analysis indicated ( Figure 5) that the DBH had the highest proportion of genetic variance among the three traits and that height had the smallest for C. fargesii f. duclouxii. This result implied that the variation due to genetic effects was greater for DBH than for height. The proportions of genetic variance in height, DBH and stem volume were higher in C. bungei than in C. fargesii f. duclouxii. In addition, the variation in the year×clone effect on the three traits was greater for C. bungei than for C. fargesii f. duclouxii, indicating that the GEI of C. bungei may be greater than that of C. fargesii f. duclouxii. The results of the broad-sense repeatability estimation showed that the height repeatability of C. fargesii f. duclouxii was only 0.223 (Figure 6), indicating a low degree of genetic control. The repeatability of stem volume for the two species was high, suggesting that genetic improvements in volume are possible.

Analyses of Growth Traits in the Two Species
The ANOVA showed that the height, DBH and stem volume of the two species were significantly different at the 0.01 level among clones and blocks and that year × clone had a significant effect at the 0.01 level on all these traits except height in C. fargesii f. duclouxii, where the interaction effect was significant at the 0.05 level (Table 3). These findings indicated that (1) the clones of the two species showed significant variation, which indicated the selection of clones could be performed with high reliability, and (2) GEIs were significant in the two species. Thus, an assessment of the stability of clone growth was necessary.
The variance components analysis indicated ( Figure 5) that the DBH had the highest proportion of genetic variance among the three traits and that height had the smallest for C. fargesii f. duclouxii. This result implied that the variation due to genetic effects was greater for DBH than for height. The proportions of genetic variance in height, DBH and stem volume were higher in C. bungei than in C. fargesii f. duclouxii. In addition, the variation in the year×clone effect on the three traits was greater for C. bungei than for C. fargesii f. duclouxii, indicating that the GEI of C. bungei may be greater than that of C. fargesii f. duclouxii. The results of the broad-sense repeatability estimation showed that the height repeatability of C. fargesii f. duclouxii was only 0.223 (Figure 6), indicating a low degree of genetic control. The repeatability of stem volume for the two species was high, suggesting that genetic improvements in volume are possible.

Analysis of Increment of Stem Volume in the Two Species
The C. bungei clone 22-03 had the maximum increment of stem volume (0.0319 m 3 ) among the C. bungei clones, with a value 164.28% higher than the minimum increment, exhibited by clone 7-01 ( Table 4). The variation coefficient of clone 16-04 (51.18%) was the smallest among all of the C. bungei clones. However, its mean increment of stem volume (0.0209 m 3 ) was lower than the population value (0.0222 m 3 ). This result suggested that for clone 16-04, the increment of stem volume was stable but was associated with a very low growth rate. For C. fargesii f. duclouxii (Table 5), the largest increment of stem volume (0.0248 m 3 ) was found in clone 63 and was 82.35% higher than the minimum increment (in clone 110). Clone 74 had the minimum variation coefficient (28.48%). However, its increment of stem volume (0.0137 m 3 ) was very low. We found that the mean increment of stem volume of C. bungei was 32.30% higher than that of C. fargesii f. duclouxii. In contrast, the mean variation coefficient of C. fargesii f. duclouxii (48.66%) was lower than that of C. bungei (65.57%). The multiple comparison tests of stem volume of clones was also performed (Tables S3 and S4). The results showed that the 22-03 had the highest stem volume in 2009 to 2014 for C. bungeii. And the 63 had the highest stem volume in 2010 to 2014 for C. fargesii f. duclouxii. It indicated that the two clones maybe the optimal clones, but their yield stability still need to be evaluated.  According to Francis and Kannenberg's [24] method, the variation coefficient of increment of stem volume was used as the abscissa, the increment of stem volume was used as the ordinate, and their means were used as boundaries to create a scatterplot to define clone yield and stability. Four groups were established for each species (Figure 7): Group I had a high increment but low stability, Group II had a high increment and high stability, Group III had a low increment but high stability, and Group IV had a low increment and low stability. Accordingly, 22-03, 1-1, 20-06, 20-07, and 16-05 of  C. bungei and 63, 128, 26, 48, 43, and 60 of C. fargesii f. duclouxii were selected as high-increment and high-stability clones.
Forests 2018, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/forests According to Francis and Kannenberg's [24] method, the variation coefficient of increment of stem volume was used as the abscissa, the increment of stem volume was used as the ordinate, and their means were used as boundaries to create a scatterplot to define clone yield and stability. Four groups were established for each species (Figure 7): Group I had a high increment but low stability, Group II had a high increment and high stability, Group III had a low increment but high stability, and Group IV had a low increment and low stability. Accordingly, 22-03, 1-1, 20-06, 20-07, and 16-05  of C. bungei and 63, 128, 26, 48, 43, and 60 of C. fargesii f. duclouxii were selected as high-increment and high-stability clones.

Stability and Increment of Stem Volume of Clones Analyzed by GGE Biplots
It was of interest to identify those genotypes for which a significant GEI was found, as these represent genotypes that adapted to the environment. A GGE biplot model was used to identify the clone that performed best in each year. All vertex clones were connected form a polygon; then, starting from the origin, vertical lines to the sides of the polygons were drawn, and the polygons were divided into multiple sectors. Each sector contained some clones and years or only clones. The vertex clone in each sector represented the highest-yielding clone in the years that fell within that particular sector. According to this rule, clone 1-1 was found to exhibit the highest increment of stem volume in 2014, and 22-03 had the highest increment of stem volume in 2010, 2011 and 2013. These data implied that 22-03 was an excellent clone with high increment of stem volume and stability. The sector containing Y2012 had two vertex clones, 19-01 and 22-08, indicating that these two clones had unique adaptability to the weather conditions in 2012. No year fell into the sector in which 7-01 and 22-10 were the vertex clones, indicating that these clones had the lowest increment of stem volume in all years tested (Figure 8a). In C. fargesii f. duclouxii, clone 63 was found to have the highest increment of stem volume in 2010-2012, and clones 110 and 15 were had the highest increments in 2013 and 2014, respectively.

Stability and Increment of Stem Volume of Clones Analyzed by GGE Biplots
It was of interest to identify those genotypes for which a significant GEI was found, as these represent genotypes that adapted to the environment. A GGE biplot model was used to identify the clone that performed best in each year. All vertex clones were connected form a polygon; then, starting from the origin, vertical lines to the sides of the polygons were drawn, and the polygons were divided into multiple sectors. Each sector contained some clones and years or only clones. The vertex clone in each sector represented the highest-yielding clone in the years that fell within that particular sector. According to this rule, clone 1-1 was found to exhibit the highest increment of stem volume in 2014, and 22-03 had the highest increment of stem volume in 2010, 2011 and 2013. These data implied that 22-03 was an excellent clone with high increment of stem volume and stability. The sector containing Y2012 had two vertex clones, 19-01 and 22-08, indicating that these two clones had unique adaptability to the weather conditions in 2012. No year fell into the sector in which 7-01 and 22-10 were the vertex clones, indicating that these clones had the lowest increment of stem volume in all years tested (Figure 8a). In       There was no overall consistency between-clone yield and stability. To address this problem, the GGE biplot was used to predict an ideal variety. The center of the multiple concentric circles represented the ideal variety ( Figure 10). The closer to the smallest concentric circle, the better is the clone. The top 5 clones were 19-27, 20-01, 22-03, 20-06, and 22-01 for C. bungei ( Figure 10a) and 63, 128, 111, 26, and 48 for C. fargesii f. duclouxii (Figure 10b). There was no overall consistency between-clone yield and stability. To address this problem, the GGE biplot was used to predict an ideal variety. The center of the multiple concentric circles represented the ideal variety ( Figure 10). The closer to the smallest concentric circle, the better is the clone. The top 5 clones were 19-27, 20-01, 22-03, 20-06, and 22-01 for C. bungei ( Figure 10a) and 63, 128, 111, 26, and 48 for C. fargesii f. duclouxii (Figure 10b).

Identification of Optimal Clones
Using the Francis and Kannenberg method in combination with the GGE biplot, we identified 1 optimal clone for C. bungei and 2 optimal clones for C. fargesii f. duclouxii ( Table 6). The mean height of the optimal clones of C. bungei and C. fargesii f. duclouxii in the 6th year were 8.10 m and 7.39 m, respectively. The genetic gain, which was 3.81% and 0.57% for C. bungei and C. fargesii f. duclouxii, respectively, was low for this trait. The genetic gain of DBH was 14.32% and 11.13% for C. bungei and C. fargesii f. duclouxii, respectively, which was much higher than that for height. The genetic gain of stem volume can potentially reach 31.55% and 22.67% for C. bungei and C. fargesii f. duclouxii, respectively. Thus, stem volume has the potential for large genetic improvement via the selection of suitable clones.

Identification of Optimal Clones
Using the Francis and Kannenberg method in combination with the GGE biplot, we identified 1 optimal clone for C. bungei and 2 optimal clones for C. fargesii f. duclouxii ( Table 6). The mean height of the optimal clones of C. bungei and C. fargesii f. duclouxii in the 6th year were 8.10 m and 7.39 m, respectively. The genetic gain, which was 3.81% and 0.57% for C. bungei and C. fargesii f. duclouxii, respectively, was low for this trait. The genetic gain of DBH was 14.32% and 11.13% for C. bungei and C. fargesii f. duclouxii, respectively, which was much higher than that for height. The genetic gain of stem volume can potentially reach 31.55% and 22.67% for C. bungei and C. fargesii f. duclouxii, respectively. Thus, stem volume has the potential for large genetic improvement via the selection of suitable clones.

Genetic Variation of C. bungei and C. fargesii f. duclouxii Clones
This study aimed to evaluate the genetic parameters of growth traits in C. bungei and C. fargesii f. duclouxii in Henan Province in China and to explore the effect of genotype on growth patterns over years. The height and DBH of the clones were measured annually. The results showed that growth pattern and environmental adaptive ability differed between C. bungei and C. fargesii f. duclouxii. The growth of C. bungei exceeded that of C. fargesii f. duclouxii from the 4th year as represented by all traits. C. bungei showed stronger growth potential than C. fargesii f. duclouxii. As C. bungei is native to the Yellow River basin, it is understandable that C. bungei had a better response than C. fargesii f. duclouxii to the weather and soil conditions of the study area. Furthemore, C. fargesii f. duclouxii was distributing in environments with a much greater range of variation (Table 1) and it forced the species to be more plastic and thus exhibit potentially lower heritability values. Some reports also showed that fluctuations in the environment have major impact on the response of a population to environmental change and the potential for plasticity to evolve is facilitated after exposure to environmental fluctuations [25]. The mean repeatability of stem volume of C. bungei and C. fargesii f. duclouxii from 2010 to 2014 was high (0.72) and intermediate (0.58), respectively. A high repeatability estimate indicates that the selection of the trait in question would be effective and minimally influenced by environmental effects [11]. These findings suggest that stem volume in the two species can be improved by artificial selection.
In addition, the PCVs of growth traits in C. fargesii f. duclouxii were higher than those in C. bungei, whereas the GCVs of growth traits in C. fargesii f. duclouxii decreased or remained stable. The GCVs of height and stem volume were generally higher in C. bungei than in C. fargesii f. duclouxii. All of these findings provided further evidence to support that the influence of environment each year on C. fargesii f. duclouxii growth was strong, whereas the growth of C. bungei was more under genetic control than under environmental control. No consistent pattern in the genetic parameters of the 1-year-old trees was observed. The most likely reason for this finding was that the ramets were at the rooting stage in the first year. The unstable growth stage significantly limited the accuracy of genetic parameter estimation. Overall, our results indicated that there were significant differences in growth traits between species and among clones. These data provide a good foundation for genetic improvement.

Genotype Effect and Genotype and Environment Interaction
Plant growth is highly dependent on environmental conditions [26], and each species occupies a unique ecological niche in time and space; that is, it forms a unique, stable relationship with the environment [27]. For example, annual rainfall can affect the plant distribution [28,29], and effective temperature affects physiological functions [30,31]. The environment varies, even in the same place among years. Plants can perceive environmental changes and respond to them. Differences between species in their response to environmental fluctuations cause asynchronized growth series and within-species variability of responses also may impact the stabilizing effect of growth asynchrony [32]. In this study we already found that the two kinds of trees have different growth responses to the same environment. The genetic effect is the main cause of this phenomenon, the C. bungei native the test site, its genetic factors regulate the body to adapt to the special environment. So a good genotype is crucial for breeding. However, except genectic effect, GEI can't also be ignored. Revealing the mechanisms underlying genotype and environment interactions can greatly benefit forest breeding and selection. To do so, it is necessary to study the responses of clones to different environments and select clones with steady yields [15,33,34]. The GEI model can help tree breeders design effective breeding programs and select suitable genotypes for a given environment [4]. In trees, GEIs are widespread. Meier et al. [35] found that annual variation in the environment significantly impacted wood formation in Douglas fir (Pseudotsuga menziesii) clones. Studies of clones of white poplar [36], Michelia chapensis [37] and River red gum (Eucalyptus camaldulensis) [38] have also indicated significant GEI effects. In this study, we examined the GEIs of C. bungei and C. fargesii f. duclouxii clones. We found significant year and clone effects. A GGE biplot allows the visual interpretation of GEI [23,39,40]. We used GGE biplots to readily identify differences in the increment of stem volume and stability among clones and a GGE model to further analyze the GEI effect. According to the analyses, among C. bungei clones, clone 22-03 had the highest mean increment of stem volume and the highest values at 1, 2 and 4 years old. These results indicated that 22-03 was a high stability clone. In C. fargesii f. duclouxii, clones 63 and 128 had both high yield and high stability when we evaluated wood yield and stability independently.

Conclusions
Genetic variation is the precondition for genetic improvement. In this study, growth traits were significantly different between species and among clones. The C. bungei clones had greater growth potential than the C. fargesii f. duclouxii clones. Height, DBH and stem volume were all significantly larger in C. bungei than in C. fargesii f. duclouxii after 4 years of age. Moreover, the stem volume repeatability was intermediate or high in the two species, indicating that clone selection would be effective. The comparison of the genetic parameters between the two species showed that the growth of C. bungei was controlled more by genetic effects than environmental effects.
GEI is a very important factor for selecting breeding strategies. Our analysis indicates the two Catalpa species both have significant GEIs for increment of stem volume. Using GGE biplots, we found that wood yield and stability are largely independent in the C. bungei clones. However, clones 63 and 128 of C. fargesii f. duclouxii had both high wood yield and high stability. As each model has limitations, we combined Francis and Kannenberg's method with GGE biplot analysis to minimize error. C. bungei clones 22-03 and C. fargesii f. duclouxii clones 63 and 128, which adapted to the diverse climatic conditions in the experimental site and presented high yield, were identified as optimal clones. Supplementary Materials: The following are available online at http://www.mdpi.com/1999-4907/10/1/57/s1, Table S1. ANOVA of growth traits of clones for C. Bungei , Table S2. ANOVA of growth traits of clones for C. fargesii f. duclouxii, Table S3. Multiple comparison of stem volume of clones for C. Bungei, Table S4. Multiple comparison of stem volume of clones for C. fargesii f. duclouxii.

Author Contributions:
This study was carried out with collaboration among all authors. J.W. and W.M. conceived and designed the experiments; Y.X., N.W., W.Z. and Q.W. performed the experiments; G.Q. and N.L. carried out data correction; L.K. and Z.W. carried out manuscript revision; and Y.X. wrote the paper.