Establishment of Regional Phytoremediation Buffer Systems for Ecological Restoration in the Great Lakes Basin, USA. II. New Clones Show Exceptional Promise

: Poplar tree improvement strategies are needed to enhance ecosystem services’ provisioning and achieve phytoremediation objectives. We evaluated the establishment potential of new poplar clones developed at the University of Minnesota Duluth, Natural Resources Research Institute (NRRI) from sixteen phytoremediation buffer systems (phyto buffers) (buffer groups: 2017 × 6; 2018 × 5; 2019 × 5) throughout the Lake Superior and Lake Michigan watersheds. We divided clones into Experimental (testing stage genotypes) and Common (commercial and/or research genotypes) clone groups and compared them with each other and each NRRI clone (NRRI group) at the phyto buffers. We tested for differences in clone groups, phyto buffers, and their interactions for survival, health, height, diameter, and volume from ages one to four years. First-year survival was 97.1%, with 95.5%, 96.2%, and 99.6% for the 2017, 2018, and 2019 buffer groups, respectively. All trees had optimal health. Fourth-year mean annual increment of 2017 buffer group trees ranged from 2.66 ± 0.18 to 3.65 ± 0.17 Mg ha − 1 yr − 1 . NRRI clones ‘99038022’ and ‘9732-31’ exhibited exceptional survival and growth across eleven and ten phyto buffers, respectively, for all years. These approaches advance poplar tree improvement efforts throughout the region, continent, and world, with methods informing clonal selection for multiple end-uses, including phytotechnologies.


Introduction
The Great Lakes Basin is one of the most important natural resources in North America, providing numerous environmental, economic, and societal benefits. Zalesny et al. [1] elaborated on these benefits, in addition to the substantial role of the Basin in provisioning freshwater and related ecosystem services to millions of people each year [2,3]. This unique water resource, however, is becoming increasingly degraded by anthropogenic activities. Legacy pollution, urban runoff and stormwater, and agricultural inputs (i.e., herbicides, pesticides, nutrients) have all contributed to declining water quality of the Basin, leading to 99% of the surface water being impaired for one or more designated use(s) [4]. generalist growth performance. Another poplar clonal regional testing network was established in 1995, 1997, and 2000 across Iowa, Michigan, Minnesota, and Wisconsin [28]. This MET network initially contained 42 clones but was expanded to a total of 187 clones, most of which were from the aforementioned Midwestern breeding programs [33]. Results from these METs showed greater biomass productivity rates than any previously recorded in the region, leading Riemenschneider et al. [28] to conclude the need for continued tree improvement activities. Significant G × E interactions defined generalist ('NC14105', 'Crandon', 'NM2') and specialist ('7300501', '80 × 01015', 'NC14103') clones [33], which have since been tested for ecosystem services and environmental technologies [16,34].
The most recent poplar breeding and testing has been conducted at the University of Minnesota Duluth, Natural Resources Research Institute (NRRI) [35,36]. In parallel with traditional clonal testing of poplar productivity through evaluation of genotypic growth and stability [36], NRRI researchers have tested the application of different silvicultural measures [37] and defined geo-robust clones (i.e., extreme generalists) for establishment across broader latitudinal and longitudinal ranges [38]. A contemporary goal of this and other poplar breeding efforts is to test clones for a wide range of ecosystem services such as carbon sequestration and phytoremediation [17,39].
Poplars have been tested and deployed extensively in phytoremediation systems to remediate organic [9,[40][41][42][43] and inorganic contaminants [44][45][46][47], in addition to newer classes of pollutants such as contaminants of emerging concern (CECs) [48][49][50]. Testing poplar clones for phytoremediation is a complex process including breeding and selection for: (1) traditional traits related to growth and productivity [51][52][53]; (2) tolerance of contaminants, determined by investigating physiological and metabolic processes [42,43,47,54]; and (3) phytoremediation potential exhibited by contaminant accumulation/degradation [41,55,56]. Simultaneous selection for such a broad range of breeding traits can be achieved with phyto-recurrent selection, a stepwise testing process. In this method, crop and tree improvement strategies are implemented over multiple testing cycles to identify and select clones with superior performance [14,57]. Throughout the selection process, the number of clones decreases while the number of tested parameters and cycle length increase. Selection using basic traits such as growth and root:shoot ratio is enhanced with data on additional parameters such as tree health and growth performance index [58]. Further investigation often includes greenhouse and field-testing clonal performance related to contaminant effects and accumulation, ecophysiology, and morpho-anatomical changes [45,46]. Following multiple selection cycles in the greenhouse, field validation of selected clones is a necessary step in phyto-recurrent selection. For example, testing clones used in the current study, Zalesny and Bauer [59] reported broad clonal variation across eleven-year-old trees grown for nitrate phytoremediation in the Midwestern US. These phyto-recurrent selection results further emphasize the importance of long-term phytoremediation studies in evaluating clonal performance throughout stand development [17].
As described by Zalesny et al. [1], phyto-recurrent selection was used to establish an ongoing MET testing network consisting of sixteen phytoremediation buffer systems (i.e., phyto buffers) at sites located in the Lake Superior (i.e., Michigan's Upper Peninsula) and Lake Michigan (i.e., eastern Wisconsin) watersheds. Given the potential of new genotypes in the biomass productivity networks illustrated above, our overarching objective in the current study was to test for ecological restoration potential of new clones developed at NRRI. To do so , we divided clones into Experimental (i.e., genotypes with a rich history of testing but are still at the experimental stage) and Common (i.e., genotypes commonly used for commercial and/or research purposes in the region) clone groups that we then compared with each other and each NRRI clone planted at the phyto buffers. Although Zalesny et al. [1] compared individual clones, these current comparisons are warranted because poplar clones in the Midwestern United States are often selected in groups based on stage of testing (i.e., Experimental versus Common) rather than individually, due to uncertainties with nursery production and availability of clonal material. Specifically , we tested for differences in the three clone groups (i.e., NRRI, Experimental, Common), phyto buffers (i.e., environments), and their interactions for health, height, diameter, and volume during early field establishment (i.e., from one to four years after planting). These data are useful to advance poplar tree improvement efforts throughout the region, continent, and world, informing clonal selection for multiple end-uses, including phytotechnologies.

Site Description
Zalesny et al. [1] provided a detailed description of the regional phytotechnologies network tested in the current study, including climate-and soil-related information. In summary, there were sixteen phytoremediation buffer systems (i.e., phyto buffers) established across ten field testing sites in 2017 (×6 phyto buffers), 2018 (×5), and 2019 (×5) in the Lake Superior watershed of the Upper Peninsula of Michigan, USA and the Lake Michigan watershed of eastern Wisconsin, USA ( Figure 1). The sites ranged in latitude from 46.7840 to 42.8382 • N and in longitude from −89.1291 to −86.5976 • W. Twenty-year (2000 to 2020) historical monthly averages for precipitation and temperature were obtained from the National Oceanic and Atmospheric Administration (NOAA) National Climate Data Center (https://www.ncdc.noaa.gov/cdo-web/ (accessed on 20 January 2021)) and are listed in Table 1. Table 2 provides buffer-specific soil properties that were acquired from the USDA Natural Resources Conservation Service (NRCS) Web Soil Survey (https://websoilsurvey.sc.egov.usda.gov/ (accessed on 20 January 2021)).

Clone Selection
Rogers et al. [58] and Zalesny et al. [1] described the phyto-recurrent selection process that was used to choose genotypes for phyto buffer field establishment. Twelve clones were selected, outplanted, and tested for each of three buffer groups (i.e., with buffer groups defined as phyto buffers established in 2017 (×6), 2018 (×5), and 2019 (×5)), and separate analyses were conducted for each buffer group for the particular set of twelve clones. Based on the objective of the current study, clones were categorized into three clone groups: (1) 'NRRI' clones that are new genotypes produced by the University of Minnesota Duluth, Natural Resources Research Institute (NRRI), in Duluth, Minnesota, USA [36,38] (these genotypes were not combined with one another and were analyzed individually, collectively representing the NRRI clone group); (2) 'Experimental' clones that have been tested broadly in the region but have not reached commercial status (combined for current analyses); and (3) 'Common' clones that have been used in decades of testing and deployment in the Midwestern United States (combined). Clones, genomic groups, and their respective clone groups are listed in Table 3. Table 3. Clone groups and buffer groups (i.e., years of planting) of clones and their genomic groups for Populus genotypes tested in a regional phytotechnologies network of sixteen phytoremediation buffer systems (i.e., phyto buffers) established from 2017 to 2019 in the Lake Superior watershed of the Upper Peninsula of Michigan, USA and the Lake Michigan watershed of eastern Wisconsin, USA.

NRRI
Experimental Common NM5 'NM' 9732-36 'DN' a Genomic groups: P. deltoides Bartr. Ex Marsh 'D'; P. deltoides × P. maximowiczii A. Henry 'DM'; P. deltoides × P. nigra L. 'DN'; P. nigra × P. maximowiczii 'NM'; b 'NRRI' = promising genotypes bred, tested, and selected at the University of Minnesota Duluth, Natural Resources Research Institute (NRRI) for broad-ranging applications [36,38]; analyzed individually. 'Experimental' = genotypes with a rich history of testing but that are still at the experimental stage; analyzed as a group. 'Common' = genotypes commonly used for commercial and/or research purposes in the region; analyzed as a group.

Phyto Buffer Establishment and Experimental Design
Individual phyto buffers were established during May and June in 2017, 2018, and 2019 by planting 25.4 cm, dormant, unrooted hardwood cuttings that were soaked in water to a height of 16.93 cm for 48 h in a dark room at 21 • C before planting. Site preparation consisted of removing rocks and other obstructions followed by tilling to a depth of 30 cm. For site maintenance, soils were tilled to a depth of 30 cm, rocks and other obstructions were continually removed, and vegetation was removed via hand weeding to a minimum diameter of 0.61 m around each individual tree. At least one maintenance entry per month was performed at each phyto buffer throughout each growing season.
The experimental design consisted of eight randomized complete blocks (RCBD) and twelve clones per block at a spacing of 2.44 × 2.44 m (i.e., 1680 trees ha −1 ). There was one exception: four blocks were planted at Slinger, Wisconsin due to space constraints. Two border rows were established on the perimeter of each phyto buffer to reduce potential border effects [60,61]. All phyto buffers were fenced using 2.3 m tall Trident extra strength deer fencing (Trident Enterprises, Waynesboro, PE, USA) to eliminate potential impacts from white-tailed deer (Odocoileus virginianus Zimmerman) browse. Replanting of dead trees with identical clones occurred each growing season to ensure full stocking of 1680 trees ha −1 . Analyses did not include the replanted trees.

Field Measurements
Tree height (to the nearest 0.1 m) and diameter (to the nearest 0.1 cm) were measured after each growing season. Height was consistently measured from the ground to the apical bud, whereas diameter measurements changed as trees aged. At one and two years after planting, diameter was measured at 10 cm above the soil surface; starting in year three, diameter at breast height (i.e., DBH at 1.37 m) was determined. Based on height (H) and diameter (D; including one-and two-year diameter and DBH), tree volume (V) was calculated using the following equation provided by Kershaw et al. [62]: V = D 2 × H. After four years of growth, the 2017 buffer group trees were too tall to be measured to the nearest 0.1 m. For these trees, DBH values were used to estimate mean annual increment (MAI; Mg ha −1 yr −1 ) according to genomic-group specific coefficients from Headlee and Zalesny [63] applied in the following model: Biomass Individual Tree = 10 a0 × DBH a1 . Standard metric conversion factors and the stocking of 1680 trees ha −1 were used to scale these individual-tree values to stand-level MAI.

Health Assessments
Six tree health parameters were scored by two researchers to reduce variability in the ratings: (1) vigor, (2) defoliation, (3) leaf discoloration, (4) chlorosis, (5) leaf scorch, and (6) leaf spots. Scoring consisted of a five-category qualitative scale ranging from 1 to 5, where 1 = optimal health, 2 = good health, 3 = moderate health, 4 = poor health, and 5 = dead (modified from Rogers et al. [58]; i.e., health score was inversely related to health). Final health index values were calculated using a multiplicative weighted summation index with a coefficient of 0.25 for vigor and 0.15 for all other parameters. Health assessments were not conducted in 2020.

Data Analysis
Clone groups described above and listed in Table 3 (i.e., NRRI, Experimental, Common) were substituted for clones in Zalesny et al. [1]; otherwise, data analysis methods were the same for both studies.
As directly reported in Zalesny et al. [1], "Health (of all buffer groups) and MAI (of the 2017 buffer group) data were subjected to analyses of variance (ANOVA) and analyses of means (ANOM) using SAS ® ( (1), un) were tested in PROC MIXED to determine which one provided the best model fit based on the lowest Bayesian Information Criterion (BIC) scores. Using these covariance structures, ANOVA were conducted in PROC MIXED for all traits, and multiple comparisons analyses were conducted to identify significant differences among least-squares means for main effects and interactions as noted above".

Survival
First-year survival across all phyto buffers and clones was 97.1%, with 95.5%, 96.2%, and 99.6% survival for the 2017, 2018, and 2019 buffer groups, respectively. For the 2017 buffer group, an additional 24 trees (4.5%) were replanted due to external factors not associated with direct mortality. Specifically, three trees were coppiced due to encroachment of a powerline, 12 trees were impacted by beavers, and nine trees exhibited some level of winter dieback that was not fatal. Additionally, trees at Caledonia (East) were flooded for five days during early May of the 2018 growing season. All trees survived the flood and growth may have been impacted initially, but growth reductions were not evident during end-of-year measurements. For the 2018 buffer group, 33 trees (6.9%) were impacted by external factors, with 11 trees experiencing substantial growth reductions associated with runoff of water used to cool an adjacent mulch pile, and 22 trees having deer browse and broken tops. For the 2019 buffer group, no external factors impacted tree survival. All trees that died or were impacted were replanted to ensure full stocking of 1680 trees ha −1 in subsequent years.
For the 2017 buffer group, first-year survival ranged from 37.5 ('99059016' at Menomonee Falls (East)) to 100% (for 18 of 30 possible buffer × clone group combinations) ( Table 4). There was minimal variability across phyto buffers, with survival at Whitelaw, which had the lowest number of trees alive, being 3.1% less than Bellevue (West), the buffer with the greatest survival. The variability increased for clone groups, ranging from 77.3% ('99059016') to 100% ('99038022'), although this range in survival was driven by the fact that only 37.5% of the '99059016' trees were alive at Menomonee Falls (East). The next lowest survival for all buffer × clone group combinations was 75% for '99059016' at Caledonia (East) and Slinger. Experimental and Common clone groups exhibited at least 92.5% survival at all buffers. For the 2018 buffer group, first-year survival ranged from 87.5% ('9732-36' at Marquette) to 100% (for 21 of 30 possible buffer × clone group combinations) ( Table 4). Variability across phyto buffers was stable, with trees at Bellevue (East) and Marquette (the buffers with the lowest survival) exhibiting 3.1% fewer trees alive than at Bellevue (Central), which had the highest survival. The percentage of trees alive across clone groups increased 5.7% from the Common clones to three of the NRRI genotypes: '9732-11'; '9732-24'; and '9732-31'. With the exception of '9732-36' grown at Marquette, all NRRI clones exhibited 100% survival across buffers, whereas the lowest survival for the Experimental and Common clones was 90.6% at Manitowoc and Marquette, respectively. For the 2019 buffer group, first-year survival was 100% for all buffer × clone group combinations, with two exceptions (Table 4). Survival was 87.5% for '9732-31' at Escanaba (East) and Ontonagon (South).

Health
Buffer main effects were significant for first-year health of 2017 (p = 0.0006), 2018 (p < 0.0001), and 2019 (p < 0.0001) buffer group trees (Table S1). Health of 2017 buffer group trees measured in 2017 (i.e., HEALTH 2017(2017) ) ranged from 1.06 ± 0.02 (Whitelaw; most healthy) to 1.17 ± 0.02 (Caledonia (East); least healthy), with an overall mean of 1.11 ± 0.02 ( Figure 2). Thus, all trees were of optimal health (i.e., health index ranging from 1 to 2). Trees grown at Menomonee Falls (West) and Whitelaw were 4.8% to 9.1% significantly healthier than at the remaining phyto buffers, which were not different than each other. Whitelaw trees were also 4.6% healthier than the overall mean, and the mean was 4.7% healthier than those from Caledonia (East). Health of 2018 buffer group trees measured in 2018 (i.e., HEALTH 2018(2018) ) ranged from 1.01 ± 0.02 (Bellevue (East); most healthy) to 1.28 ± 0.02 (Manitowoc; least healthy), with an overall mean of 1.09 ± 0.02 ( Figure 2). Trees at Manitowoc had 15% unhealthier trees than Caledonia (West), and both of these buffers had significantly lower health than at Bellevue (Central), Bellevue (East), and Marquette, which were not different from one another. With the exception of Caledonia (West), all buffers exhibited health index scores significantly different than the overall mean, with Manitowoc being the only buffer with poorer health (i.e., by 15%). HEALTH 2019(2019) ranged from 1.02 ± 0.01 (Ontonagon (South); most healthy) to 1.14 ± 0.01 (Escanaba (West); least healthy), with an overall mean of 1.07 ± 0.01 (Figure 2). Trees at Escanaba (West) were significantly less healthy than those at Escanaba (East), Munising, and Ontonagon (North), the latter of which had similar health to Ontonagon (South), which exhibited 5% greater health than the overall mean. The clone group main effect was significant for HEALTH 2017(2017) (p < 0.0001) (Table S1). HEALTH 2017(2017) ranged from 1.05 ± 0.02 ['99059016'; most healthy] to 1.19 ± 0.02 [Experimental; least healthy], with an overall mean of 1.11 ± 0.02 (Figure 3). The healthiest trees were from '99059016' and the Common clone group, which did not differ from one another but were 5.7% and 4% healthier than the overall mean, respectively. Although health of the Experimental trees did not differ from '9732-36', they were of 6.8% poorer health than the overall mean.
Differences among buffer and clone main effects were significant for second-and third-year health of the 2017 buffer group trees and second-year health of the 2018 buffer group trees (p < 0.05), yet the buffer × clone group interaction governed health for all three combinations (p 2017(2018) = 0.0233; p 2017(2019) = 0.0010; p 2018(2019) = 0.0023) (Table S1). HEALTH 2017(2018) ranged from 1.20 ± 0.08 ('99059016' at Menomonee Falls (East); most healthy) to 1.76 ± 0.07 ('9732-36' at Slinger; least healthy), with an overall mean of 1.36 ± 0.05 (Figure 4). The healthiest trees were grown at Menomonee Falls (East), which had 17.8% better HEALTH 2017(2018) than at Slinger, which exhibited the poorest health. The range in health scores was narrower for clone groups, with '99059016' having 10.5% healthier trees than Experimental genotypes that had the poorest health. Three buffer × clone group interactions resulted in HEALTH 2017(2018) values that were significantly greater (i.e., of poorer health) than the overall mean: Experimental at Bellevue (West); '9732-36' and Experimental at Slinger (Figure 4). Trends in HEALTH 2017(2019) ( Figure S1) and HEALTH 2018(2019) ( Figure S2) were similar to HEALTH 2017(2018) .  Table 3 for definitions) tested in six phytoremediation buffers (i.e., phyto buffers) established in 2017 (i.e., the 2017 Buffer Group) in the Lake Michigan watershed of eastern Wisconsin, USA. Error bars represent one standard error of the mean. The dashed line represents the overall mean, and asterisks indicate means different than the overall mean at p < 0.05. Bars with different letters are different at p < 0.05. See Section 2 for complete tree health definitions (1 = optimal health, 2 = good health, 3 = moderate health, 4 = poor health, and 5 = dead).  Table 3 for definitions) tested in six phytoremediation buffer systems (i.e., phyto buffers) established in 2017 (i.e., the 2017 Buffer Group) in the Lake Michigan watershed of eastern Wisconsin, USA. The dashed line represents the overall mean, and asterisks indicate means different than the overall mean at p < 0.05. Bars with different letters across all buffer × clone group combinations are different at p < 0.05. See Section 2 for complete tree health definitions (1 = optimal health, 2 = good health, 3 = moderate health, 4 = poor health, and 5 = dead).

Biomass and Growth
Buffer main effects were significant for mean annual increment (MAI) of 2017 buffer group trees measured in 2020 (i.e., MAI 2017(2020) ) (p < 0.0001) (Table S1). MAI 2017(2020) ranged from 1.62 ± 0.18 (Whitelaw) to 3.93 ± 0.18 Mg ha −1 yr −1 (Menomonee Falls (West)), with an overall mean of 3.12 ± 0.20 Mg ha −1 yr −1 (Figure 2). The largest trees were grown at Caledonia (East), Menomonee Falls (East), Menomonee Falls (West), and Slinger; these trees were at least 23.1% significantly greater than those grown at Bellevue (West), which were 64% larger than Whitelaw trees. Trees grown at Bellevue (West) and Whitelaw had significantly less biomass than the overall mean, while those at both Menomonee Falls buffers had biomass greater than the mean.
The buffer × year interaction was significant for height, diameter, and volume of the 2017 buffer group trees, in addition to height for the 2018 and 2019 buffer group trees (p < 0.0001 for all interactions) (Table S2) Figure  S6) were similar to VOLUME 2017 for the buffer × year interaction.
The buffer × clone group × year interaction was significant for diameter (p = 0.0036) and volume (p < 0.0001) of the 2018 buffer group trees (Table S2). VOLUME 2018(2018) ranged from 15.9 ± 28.3 ('9732-11' at Marquette) to 182.1 ± 22.1 cm 3 ('9732-31' at Caledonia (West)), with an overall mean of 76.5 ± 22.7 cm 3 , whereas VOLUME 2018(2019) ranged from 383.5 ± 825.9 (Common at Marquette) to 7975.7 ± 825.9 cm 3 (Common at Manitowoc), with an overall mean of 3399.7 ± 848.2 cm 3 ( Table 5). VOLUME 2018(2020) ranged from 632.2 ± 2129.9 (Common at Marquette) to 23,912.0 ± 2129.9 cm 3 ('9732-31' at Caledonia (West)), with an overall mean of 8763.9 ± 2187.2 cm 3 ( Table 5). Across all buffer × clone group × year combinations, VOLUME 2018 increased 44.4-fold from the first year to the second year after planting, and then 2.6-fold from the second year to the third year. After the first growing season, trees with the greatest volume were grown at Caledonia (West), which had 470.3% greater volume than Marquette, the buffer with the smallest trees. For the second and third growing seasons, the largest trees were grown at Manitowoc, which had 837.1% and 1322.3% greater volume than the buffer with the smallest trees (Marquette), respectively. The range in volume was narrower for clone groups, with '9732-31' exhibiting the greatest volume in all years. For 2018, '9732-31' had 67.6% bigger trees than those of the Experimental group, which had the smallest trees. Similarly, '9732-31' produced 50.4% and 66.9% larger trees than '9732-36' in 2019 and 2020, respectively. Trends in diameter of the 2018 buffer group trees were similar to those of volume (Table S3).       [36,38]. 'Experimental' = genotypes with a rich history of testing but that are still at the experimental stage. 'Common' = genotypes commonly used for commercial and/or research purposes in the region. b BC: Bellevue (Central); BE: Bellevue (East); CW: Caledonia (West); MA: Manitowoc; MQ: Marquette.
The buffer × clone group × year interaction was significant for diameter (p = 0.0293) and volume (p < 0.0001) of the 2019 buffer group trees (Table S2). VOLUME 2019(2019) ranged from 16.4 ± 26.0 ('9732-36' at Ontonagon (North)) to 396.3 ± 25.8 cm 3 ('99038022' at Escanaba (West)), with an overall mean of 91.1 ± 25.9 cm 3 , whereas VOLUME 2019(2020) ranged from 189.0 ± 391.4 ('9732-24' at Ontonagon (North)) to 5639.8 ± 391.4 cm 3 (Common at Escanaba (West)), with an overall mean of 1294.4 ± 393.02 cm 3 (Table 6). VOLUME 2019 increased 14.2-fold from the first year to the second year after planting. For the first and second growing seasons, the largest trees were grown at Escanaba (West), which had 903.4% and 860.1% greater volume than the buffer with the smallest trees (Ontonagon (North)), respectively. Clone groups exhibited less variation, with '99038022' exhibiting the greatest first-year volume, which was 71.8% more than that of '9732-31', which had the smallest trees. The Common group trees produced 108.8% larger trees than '9732-11' at two years after planting. Trends in diameter of the 2019 buffer group trees were similar to those of volume (Table S4).

Discussion and Conclusions
Selection of Populus and other short rotation woody crop (SRWC) species to match specific site and growing conditions is imperative for maximizing productivity [64]. The availability of appropriate genotypes can be necessary for plantation or site managers in the absence of precise site information [65]. Species of Populus, a genus utilized ubiquitously for environmental applications, have been bred and tested extensively for biomass production [66], especially beginning in the early 1990s with international germplasm exchanges and other cooperative tree improvement efforts between the United States and Europe [67]. Results of these testing efforts have shown great potential of new genotypes for biomass production. Building on these successful partnerships, the poplar breeding and testing program at the University of Minnesota Duluth, Natural Resources Research Institute (NRRI) has produced thousands of genotypes since the mid-1990s [35,36]. Some of these clones have been defined as geo-robust, meaning they are extreme generalists with the capability for establishment across broader latitudinal and longitudinal ranges [38]. The ecological restoration potential of a subset of these clones was tested in the current study, and clones '99038022' and '9732-31' exhibited exceptional survival and growth across eleven and ten phytoremediation buffer systems (i.e., phyto buffers), respectively, in the Lake Superior watershed of the Upper Peninsula of Michigan, USA and the Lake Michigan watershed of eastern Wisconsin, USA. Other NRRI clones showed exceptional promise at individual phyto buffers, demonstrating the value of matching individual genotypes to specific site conditions. This combination of generalist and specialist genotypes corroborated the importance of such multi-environmental trials (MET) throughout plantation development, making the current data useful for advancing poplar tree improvement efforts throughout the region, continent, and world, informing clonal selection for multiple end-uses, including phytotechnologies.
Across the United States, average annual poplar productivity of approximately 9 Mg ha −1 yr −1 is common, with advanced genotypes exhibiting nearly 2.5 times as much growth [68]. In the Midwestern United States, the location of the current study, a wide range of poplar biomass productivity potential has been reported. Most common stand densities of 1075 and 1736 trees ha −1 (i.e., 3 × 3 and 2 × 2 m spacing, respectively) have resulted in mean annual increment (MAI) ranges similar to those of our study for the same age. Poplar biomass plantations with 1736 trees ha −1 had MAI values ranging from 2.8 to 6.1 Mg ha −1 yr −1 at four years after planting [29,32] and 6.7 to 9.0 Mg ha −1 yr −1 for five-year-old trees [30]. Maximum productivity resulting from 3-PG modeling resulted in 13.0 Mg ha −1 yr −1 at the end of ten-year rotations [69]. Plantations of the same stand density as the current study (i.e., 1075 trees ha −1 ) exhibited productivity ranging from 4.3 to 5.3 Mg ha −1 yr −1 at age four years [43] and 5.1 to 16.8 Mg ha −1 yr −1 after six years of growth [28]. Optimizing genotype × environment interactions for the best performing clones resulted in MAI values of 3.0 to 11.0 Mg ha −1 yr −1 for four-year-old trees [28]. Such a wide range in productivities can be attributed in part to site conditions and planting stock (i.e., rooted vs. unrooted cuttings). Effective clonal selection is integral to maximizing productivity, regardless of application (e.g., biomass for bioenergy, phytotechnologies, etc.). Productivity values in the lower part of this range have been shown for poplars grown for phytotechnologies. At phytoremediation plantations in the Midwest planted at stand densities from 434 to 4310 trees ha −1 , MAI values ranged from 4.4 to 15.5 Mg ha −1 yr −1 for some of the same clones as the current study ('DN5', 'DN34', 'NM2', 'NM6') [17]. However, lower productivity (0.5 to 2.5 Mg ha −1 yr −1 ) also has been reported for poplar clones 'DN5', 'NC14106', 'NM2', and 'NM6' irrigated with landfill leachate grown for two years with a stand density of 3472 trees ha −1 [52]. These results corroborated the growth productivity of clones in the current study, for which MAI ranged from 1.6 to 3.9 Mg ha −1 yr −1 across all phyto buffers and clones. Considering that phyto buffers in our study were located adjacent to landfills and similar sites, clone productivity can be considered satisfactory because the presence of potential soil heterogeneity can significantly affect biomass production of poplar clones [14,42,46,47,53,57,70].
Optimal site conditions for poplar growth include deep, fertile sandy-loam to clayloam soils with pH ranging from 5.0 to 7.5 that are well drained, but not droughty [71]. Thus, annual precipitation is another influential factor and, in the present study, all phyto buffers fit within the regional precipitation gradient range of 76.2 to 88.9 cm [30]. Site conditions at the buffers significantly affected growth and productivity of the tested clones, specifically concerning soil water availability and pH, which serve as limiting factors for poplar growth. By comparison, there was a lack of phyto buffer × clone group interaction regarding MAI at four years after planting. Such an outcome can be explained by the origin of the hybrids; NRRI clones belong to the 'DN' genomic group, whereas Control and Experimental clone groups contain clones originating from different poplar species and inter-and intra-sectional hybrids [17].
Trends in health were similar across phyto buffer groups; phyto buffer and clone group main effects governed health during the year of establishment, and in the following years, phyto buffer × clone group interactions were expressed. Such results can be explained by a stronger influence of site conditions and clone group characteristics (i.e., rooting ability) on vitality during the year of establishment, whereas the interaction of the factors evolved in subsequent years. Greenhouse experiments of Rogers et al. [58] showed a similar health response of NRRI clones '99038022' and '9732-36' compared to Experimental ('NC14106') and Common ('DN34', 'NM2', 'NM6') clones grown in soils from six of the phyto buffers of the current study (BW: Bellevue (West); CE: Caledonia (East); ME: Menomonee Falls (East); MW: Menomonee Falls (West); SL: Slinger; WH: Whitelaw). Finally, despite significant effects of phyto buffer, clone group, and their interaction, all health assessment values were within the optimal health category, with values ranging from 1.11 to 1.36 across all phyto buffer × clone group × year combinations (Figures 1-3, Figures S1 and S2; Table S1), indicating no substantial influence on clonal vitality across all sites.
As expected, the phyto buffer × clone group × year interaction for diameter and volume production of clones was significant, indicating different growth patterns of tested clones and, further, changes in annual growth increment of poplars throughout the pro-duction cycle [72]. Such an explanation could also be applied for MAI, which was lower (though not always significantly) for NRRI clones than those of the Common clone group. These results were corroborated considering volume production of the clones in the 2017 Phyto Buffer Group. NRRI clones '99059016' and '9732-36' had significantly lower wood volume than Common clones after the first year, whereas these differences were negligible after two and three years of growth. In the current study, the lack of a significant phyto buffer × clone group × year interaction for height can be explained by the fact that although height and diameter are typically positively correlated for poplars (and trees in general), this correlation is influenced by variation due to the site and G × E interactions, leading to the need for matching clones to specific site conditions [73]. In addition, different biomass allocation growth patterns (e.g., terminal vs. lateral shoot growth) among clones could have impacted the current results [64].
In general, NRRI clones showed potential for use in phytotechnologies, with high productivity exhibited for clones '99038022' and '9732-31'. Previously, NRRI clones '99038022', '99059016', '9732-11', '9732-24', and '9732-31' demonstrated high productivity for mean basal area and volume, often outperforming Common clones [36,37]. Although the productivity of NRRI clones have varied markedly across sites, the identification of geographically robust clones holds promise for efficiently meeting diverse environmental objectives [38]. Breeding and selecting clonal forest reproductive material has many advantages, including utilization of both additive and non-additive variance, resulting in larger genetic gains [35,74,75]. On the other hand, environmental factors can diminish genetic gains. According to Pliura et al. [76], the presence of a significant G × E interaction implies that: (1) a genotype's performance in a specific environment can be less accurately predicted by the overall genotypic mean, and (2) a genotype's overall performance can be less accurately predicted by the genotypic mean in a specific environment. Both of these responses can result in biased estimates and, thus, decreases in genetic gains [76].
The aforementioned results, including those of the present study, indicated that NRRI clones, which originated from a narrow range of latitudes, were well-suited to the latitudinal range of the phyto buffers. For example, 'D125' (selected from Dr. Carl Mohn's long-term P. deltoides program at the University of Minnesota) is the female Minnesota P. deltoides parent used for all F 1 full-sib progeny within family pedigree '9732'. In contrast, some genotypes of the Common and Experimental clone groups originated from other parts of North America and Europe, making them less adapted to certain phyto buffer site conditions. The intra-specific breeding strategy for NRRI clones uses P. deltoides parents of a limited geographic range (Minnesota) combined with other Aigeiros species (e.g., P. nigra) to produce progeny of increased performance [35]. The P. nigra component of 'DN' hybrids has produced a strong heterotic effect not exhibited in P. trichocarpa Torr. et Gray × P. deltoides 'TD' hybrids due to greater genomic relatedness between P. deltoides and P. nigra relative to poplars from the Tacamahaca section (e.g., P. trichocarpa, P. maximowiczii A. Henry) [77]. This genetic closeness was corroborated by mitochondrial DNA variation [78] and simple sequence repeat (SSR) markers [79]. In addition, species biology likely contributed substantially to the performance of NRRI hybrids. According to Sixto et al. [65], the plasticity of certain Aigeiros species enabled them to grow on a vast range of habitats (e.g., from poor, dry and stony to optimal silty or sandy loamy soils) versus Tacamahaca balsam poplars that preferred alluvial, fertile soils in wetter climates and higher elevations. Their results were verified by findings of positive sensitivity to increases in median temperature and negative sensitivity to increased sand content by P. nigra clones, with the opposite occurring for P. trichocarpa × P. deltoides hybrids [65]. Nelson et al. [37] hypothesized that the P. nigra male component of P. deltoides × P. nigra hybrids imparts broad adaptability to these genotypes.
Overall, in the current study, NRRI clones exhibited positive growth performance at all sixteen phyto buffers during the first four years of establishment. Their height, diameter, and volume, like those of the Common and Experimental clone groups, were influenced by site conditions, which was expected considering soil heterogeneity at the phyto buffers. NRRI clones, the progeny of Minnesota-selected P. deltoides and P. nigra, were robust and well-adapted to the varying climate and soils at the phyto buffers. Our results corroborated previous testing of NRRI clones in more traditional SRWC production plantations [35][36][37][38], indicating their potential for use in phytotechnologies.