Performance of hybrid poplar clones in short rotation coppice in Mediterranean environments: analysis of genotypic stability

Improving production in short rotation coppice (SRC) plantations requires, among other elements, a proper understanding of clonal performance. Genotypic stability over a range of environments is a factor of concern for breeding and recommendation purposes. Most common stability measures can be embedded in a mixed‐model framework accounting for interaction and heterocedasticity in genotype‐by‐environment tables. Data from nine hybrid poplars of different taxonomic background were tested in four Mediterranean sites under three agronomic practices (control, herbicide application, and supplementary fertilization) for total biomass (TB), stem biomass (SB), and branch biomass (BB) at the end of the first rotation. Stability models (stability variance, Finlay–Wilkinson and Eberhart–Russell) were compared, also allowing for the definition of groups of genotypes with distinct taxonomic backgrounds and a priori different variabilities. Results showed that genotype‐by‐environment (GE) interactions were associated with factors inherent to evaluation sites rather than to the agronomic practices tested. Depending on biomass fraction, regression models provided appropriate stability measures. Highly reactive clones to improving environmental conditions (e.g., ‘AF2’) tended to show the largest mean TB. However, this was not always the case, as clone ‘Monviso’ showed both intermediate reactivity (i.e., stable sensu Eberhart–Russell) and enhanced overall performance. The taxonomic group was relevant for explaining stability patterns for SB. The stability assessment for BB indicated different patterns in biomass allocation. Present findings point to the feasibility of either exploiting specific adaptation (in which case hybrid type may play a relevant role) or searching for broadly adapted, stable material exhibiting good performance in Mediterranean conditions.     

Physiological adaptations of five poplar genotypes grown under SRC in the semi-arid Mediterranean environment

Key message

The genotype ‘Neva’ under high plant density showed the highest biomass yield and optimal physiological strategies and could be the most suitable choice under semi-arid environment

Abstract

The poplars (Populus spp.) are the most sensitive plants to water deficit conditions among the woody species utilized for biomass production for energetic purposes; their productivity is associated with water availability in the soil. In the Mediterranean environment, crops are mainly limited by evapotranspirative demand that is not balanced by rainfall supply. As new hybrids with high growth rates and resistance to water stress are selected, the use of poplar as an energy crop may increase in Southern regions of Mediterranean Europe. The growth dynamics and physiological characteristics of poplar hybrid genotypes have been monitored for 2 years at a site with a Mediterranean climate, Apulia region, that could be used for energy crops. Unrooted cuttings of three recently selected genotypes of poplar (‘Neva’, ‘Dvina’ and ‘Lena’) and two “traditional” genotypes (‘Luisa Avanzo’ and ‘Bellini’) were planted in the spring of 2010 at two different densities: (a) low plant density = 1,667 cuttings ha^?1 (LPD); (b) high plant density = 6,667 cuttings ha^?1 (HPD). The genotypes ‘Lena’ and ‘Dvina’ showed the lowest survival rates and the poorest growth among the hybrid poplar tested. The genotype ‘Bellini’ had low stomatal sensitivity to soil water content and a moderate productive performance. The genotypes ‘Luisa Avanzo’ and ‘Neva’ had a good degree of rooting and sprouting, high values of leaf relative water content (RWC_l) and low values of stomatal conductance (g _s) during the summer months. In “Neva”, these characteristics were associated with the best yields (4 t ha^?1) in HPD.     

Integrated drought responses of black poplar: how important is phenotypic plasticity?

Climate change is expected to increase drought frequency and intensity which will threaten plant growth and survival. In such fluctuating environments, perennial plants respond with hydraulic and biomass adjustments, resulting in either tolerant or avoidant strategies. Plants' response to stress relies on their phenotypic plasticity. The goal of this study was to explore physiology of young Populus nigra in the context of a time‐limited and progressive water deficit in regard to their growth and stress response strategies. Fourteen French 1‐year‐old black poplar genotypes, geographically contrasted, were subjected to withholding water during 8 days until severe water stress. Water fluxes (i.e. leaf water potentials and stomatal conductance) were analyzed together with growth (i.e. radial and longitudinal branch growth, leaf senescence and leaf production). Phenotypic plasticity was calculated for each trait and response strategies to drought were deciphered for each genotype. Black poplar genotypes permanently were dealing with a continuum of adjusted water fluxes and growth between two extreme strategies, tolerance and avoidance. Branch growth, leaf number and leaf hydraulic potential traits had contrasted plasticities, allowing genotype characterization. The most tolerant genotype to water deficit, which maintained growth, had the lowest global phenotypic plasticity. Conversely, the most sensitive and avoidant genotype ceased growth until the season's end, had the highest plasticity level. All the remaining black poplar genotypes were close to avoidance with average levels of traits plasticity. These results underpinned the role of plasticity in black poplar response to drought and calls for its wider use into research on plants' responses to stress.     

内蒙古镶黄旗草地蝗虫潜在发生可能性评价

以内蒙古草地蝗虫产卵期、越冬期和孵化期的关键气象影响因子作为草地蝗虫气象适宜度指数构建的主要因子,对内蒙古镶黄旗2010年草地蝗虫潜在发生的气象适宜性进行评价;根据当年7月上中旬在镶黄旗的实地调查资料,选取海拔、坡向、土壤类型、土壤含砂量、植被类型、植被盖度、土地覆被类型7个相对稳定的生境因子,用模糊评判方法和3S（GIS、RS、GPS）技术对该旗草地蝗虫潜在发生的生境适宜性进行评价;最后通过构建气象-生境适宜性综合评价模型,得到该旗2010年草地蝗虫潜在发生可能性（POG）等级,并用2010年实测数据和2001-2010年历史数据对模型模拟的蝗虫发生位置和蝗灾发生面积进行验证.结果表明：用本文所建气象-生境适宜性综合评价模型对镶黄旗POG等级的评价结果是可靠的.该旗草地蝗虫潜在发生的气象适宜性等级非常一致,绝大多数为适宜等级;蝗虫潜在发生源地的空间异质性主要与生境因子有关,在海拔1300～1400 m的平地/东坡/南坡、植被盖度30%～50%的温带丛生禾草草原、土壤含砂量60%～80%的典型栗钙土的生境条件下,草地蝗虫潜在发生的可能性最高.     

Ectomycorrhizal Colonization and Diversity in Relation to Tree Biomass and Nutrition in a Plantation of Transgenic Poplars with Modified Lignin Biosynthesis

Wood from biomass plantations with fast growing tree species such as poplars can be used as an alternative feedstock for production of biofuels. To facilitate utilization of lignocellulose for saccharification, transgenic poplars with modified or reduced lignin contents may be useful. However, the potential impact of poplars modified in the lignification pathway on ectomycorrhizal (EM) fungi, which play important roles for plant nutrition, is not known. The goal of this study was to investigate EM colonization and community composition in relation to biomass and nutrient status in wildtype (WT, Populus tremula × Populus alba) and transgenic poplar lines with suppressed activities of cinnamyl alcohol dehydrogenase, caffeate/5-hydroxyferulate O-methyltransferase, and cinnamoyl-CoA reductase in a biomass plantation. In different one-year-old poplar lines EM colonization varied from 58% to 86%, but the EM community composition of WT and transgenic poplars were indistinguishable. After two years, the colonization rate of all lines was increased to about 100%, but separation of EM communities between distinct transgenic poplar genotypes was observed. The differentiation of the EM assemblages was similar to that found between different genotypes of commercial clones of Populus × euramericana. The transgenic poplars exhibited significant growth and nutrient element differences in wood, with generally higher nutrient accumulation in stems of genotypes with lower than in those with higher biomass. A general linear mixed model simulated biomass of one-year-old poplar stems with high accuracy (adjusted R² = 97%) by two factors: EM colonization and inverse wood N concentration. These results imply a link between N allocation and EM colonization, which may be crucial for wood production in the establishment phase of poplar biomass plantations. Our data further support that multiple poplar genotypes regardless whether generated by transgenic approaches or conventional breeding increase the variation in EM community composition in biomass plantations.     

Generalists versus specialists in fluctuating environments: a bet-hedging perspective

Bet-hedging evolves in fluctuating environments because long-term genotype success is determined by geometric (rather than arithmetic) mean fitness across generations. Diversifying bet-hedging produces different specialist offspring, whereas conservative bet-hedging produces similar generalist offspring. However, many fields, such as behavioral ecology and thermal physiology, typically consider specialist versus generalist strategies only in terms of maximizing arithmetic mean fitness benefits to individuals. Here we model how environmental variability affects optimal amounts of phenotypic variation within and among individuals to maximise genotype fitness, and we disentangle the effects of individual-level optimization and genotype-level bet-hedging by comparing long-term arithmetic versus geometric mean fitness. For traits with additive fitness effects within lifetimes (e.g. foraging-related traits), genotypes of similar generalists or diversified specialists perform equally well. However, if fitness effects are multiplicative within lifetimes (e.g. sequential survival probabilities), generalist individuals are always favored. In this case, geometric mean fitness optimization requires even more within-individual phenotypic variation than does arithmetic mean fitness, causing individuals to be more generalist than required to simply maximize their own expected fitness. In contrast to previous results in the bet-hedging literature, this generalist conservative bet-hedging effect is always favored over diversifying bet-hedging. These results link the evolution of behavioral and ecological specialization with earlier models of bet-hedging, and we apply our framework to a range of natural phenomena from habitat choice to host specificity in parasites.     

Detecting a difference – assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants

There is current debate on whether genetically-manipulated plants might contain unexpected, potentially undesirable, changes in overall metabolite composition relative to that of the progenitor genotype. However, appropriate analytical technology and acceptable metrics of compositional similarity require development, particularly to allow data integration from different laboratories and different harvests. For an initial comprehensive overview of compositional similarity, we explored the use of a rapid and relatively non-selective fingerprinting technique based on flow injection electrospray ionisation mass spectrometry (FIE-MS). Six conventionally-bred potato cultivars and six experimental bioengineered potato genotypes were produced in four field blocks during two growing seasons and analysed on two different analytical instruments (LCT, Micromass in 2001 and LTQ, Thermo Finnigan in 2003). Field effects and overall process variability was found to be negligible when compared to inherited genotype variance. The data derived separately for experiments using tubers from individual harvest years were compared to assess the generalisability of models for the comparison of GM and non-GM potato tubers under investigation. This procedure proved appropriate for not only rapid assessment of similarities between plant genotypes but also to predict the identity of metabolite signals that could explain differences between genotype classes irrespective of the instrument used for analysis. Importantly, despite differences in ionisation and data acquisition properties of the two instruments the generalisation of models could be confirmed after correlation analysis of explanatory variables correctly identified the molecular origin of differences between genotypes. We conclude that FIE-MS metabolomics fingerprinting technology coupled to machine learning data analysis has great potential as a robust tool for first-pass metabolic phenotyping and, therefore, initial assessments of compositional similarities prior to use of more targeted hyphenated gas or liquid chromatography-mass spectrometry techniques.     

Population genetic structure and connectivity of the harmful dinoflagellate Alexandrium minutum in the Mediterranean Sea

The toxin-producing microbial species Alexandrium minutum has a wide distribution in the Mediterranean Sea and causes high biomass blooms with consequences on the environment, human health and coastal-related economic activities. Comprehension of algal genetic differences and associated connectivity is fundamental to understand the geographical scale of adaptation and dispersal pathways of harmful microalgal species. In the present study, we combine A. minutum population genetic analyses based on microsatellites with indirect connectivity (C(i)) estimations derived from a general circulation model of the Mediterranean sea. Our results show that four major clusters of genetically homogeneous groups can be identified, loosely corresponding to four regional seas: Adriatic, Ionian, Tyrrhenian and Catalan. Each of the four clusters included a small fraction of mixed and allochthonous genotypes from other Mediterranean areas, but the assignment to one of the four clusters was sufficiently robust as proved by the high ancestry coefficient values displayed by most of the individuals (>84%). The population structure of A. minutum on this scale can be explained by microalgal dispersion following the main regional circulation patterns over successive generations. We hypothesize that limited connectivity among the A. minutum populations results in low gene flow but not in the erosion of variability within the population, as indicated by the high gene diversity values. This study represents a first and new integrated approach, combining both genetic and numerical methods, to characterize and interpret the population structure of a toxic microalgal species. This approach of characterizing genetic population structure and connectivity at a regional scale holds promise for the control and management of the harmful algal bloom events in the Mediterranean Sea.     

Effect of Seasonal Changes on Predictive Model Assessments of Streams Water Quality with Macroinvertebrates

In this study we investigate how seasonal variability in aquatic macroinvertebrate communities affects the performance of a predictive model developed to assess environmental quality. Macroinvertebrates were sampled from nine not visibly disturbed sites located in different streams of the Mondego catchment across a full year. Organisms were identified to the lowest practicable taxonomic level and their abundances recorded at three taxonomic levels (order, family and lowest level). The seasonal samples were examined with regard to seasonal variation using three predictive models at order, family and lowest taxonomic level. The models showed increasing effect of seasonal changes across taxonomic levels, from order to the lowest level. When using the current models samples should be taken in the same season as the reference sites were sampled. Furthermore, data from more reference sites should be added to the model in order to encompass sufficient natural variation and allow the use of the model in different seasons. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Water use of a multigenotype poplar short‐rotation coppice from tree to stand scale

Short‐rotation coppice (SRC) has great potential for supplying biomass‐based heat and energy, but little is known about SRC's ecological footprint, particularly its impact on the water cycle. To this end, we quantified the water use of a commercial scale poplar (Populus) SRC plantation in East Flanders (Belgium) at tree and stand level, focusing primarily on the transpiration component. First, we used the AquaCrop model and eddy covariance flux data to analyse the different components of the stand‐level water balance for one entire growing season. Transpiration represented 59% of evapotranspiration (ET) at stand scale over the whole year. Measured ET and modelled ET were lower as compared to the ET of reference grassland, suggesting that the SRC only used a limited amount of water. Secondly, we compared leaf area scaled and sapwood area scaled sap flow (F_s) measurements on individual plants vs. stand scale eddy covariance flux data during a 39‐day intensive field campaign in late summer 2011. Daily stem diameter variation (?D) was monitored simultaneously with F_s to understand water use strategies for three poplar genotypes. Canopy transpiration based on sapwood area or leaf area scaling was 43.5 and 50.3 mm, respectively, and accounted for 74%, respectively, 86%, of total ecosystem ET measured during the intensive field campaign. Besides differences in growth, the significant intergenotypic differences in daily ?D (due to stem shrinkage and swelling) suggested different water use strategies among the three genotypes which were confirmed by the sap flow measurements. Future studies on the prediction of SRC water use, or efforts to enhance the biomass yield of SRC genotypes, should consider intergenotypic differences in transpiration water losses at tree level as well as the SRC water balance at stand level.     

Comparative taxonomic structure of the floras of two Mediterranean-climate regions: Iberia and California

Two major events were invoked to understand recent biodiversity patterns in Mediterranean floras: northern hemisphere glaciations and historical human impacts. These two events were considered in this work, where we investigated general patterns in plant species richness and rarity attributes in two different Mediterranean regions: California and Iberia. Our goal was to assess whether comparisons of this sort provided evidence of different extinctions rates, making an effort to decouple anthropogenic from ice age‐related effects in both regions. We employed a taxonomically revised database for eight Mediterranean floras containing information on species richness for 298 families and rarity attributes for 11,834 taxa. We used summary statistics (Gini coefficient) and randomly generated models to test for general patterns of the distribution of diversity within and among taxonomic groups. We then used this general pattern among Mediterranean floras to provide a context in which to evaluate our two focal areas. Results indicated that floras of California and Iberia share the closest taxonomic structure among Mediterranean regions. Differences emerged in rarity attributes and the taxonomic identities of rarity rich groups. These findings were interpreted in the light of Pleistocene changes. In addition, a closer focus on rarity attributes allowed us to pinpoint some segments of these floras where anthropogenic activities may drive variation from general patterns, specifically for rare species in ecologically sensitive habitats.     

Bark morphological and chemical features are differentially correlated with disease resistance and yield in hybrid poplar taxa

In the southeastern United States, the establishment of short-rotation intensively cultured plantations of hybrid poplar has been hindered by its susceptibility to stem cankers. We evaluated the tradeoffs between biomass yield and disease tolerance in hybrid poplar genotypes belonging to P. deltoides × P. maximowiczii (DM), P. deltoides × P. nigra (DN), P. trichocarpa × P. maximowiczii (TM), and P. deltoides × P. deltoides (DD) taxa. We hypothesized that canker resistant genotypes will have thicker bark but bark thickness and biomass yield will be negatively correlated. After two growing seasons, the DD genotypes developed thicker bark compared to the genotypes of other taxa and bark thickness was not correlated with biomass yield in the DD genotypes (R² = 0.002). However, in the TM, DM, and DN genotypes, bark thickness was negatively correlated with biomass yield (R² = 0.33–0.77). Disease incidence studies revealed that the DM genotypes were most susceptible to canker whereas no disease was detected in DD genotypes. Furthermore, bark analysis conducted by Fourier transform infrared spectroscopy coupled with multivariate analysis showed that that DD genotypes to be chemically separate from the three hybrid genotypes and that bark chemistry was correlated with canker disease incidence. Taken together, these results reveal that it is possible to generate hybrid poplar genotypes with thicker bark, disease resistance, and higher biomass yields. This insight should guide further efforts to develop genetically improved hybrid poplar genotypes, both in terms of biomass yield and disease tolerance, for cultivation in the southeastern United States. Hybrid poplar cultivation in southeastern United States is hindered by its susceptibility to stem cankers. We evaluated tradeoffs between yield and canker disease resistance in various hybrid poplar genotypes. After two growing seasons, the DD genotypes showed disease resistance and developed thicker bark that was chemically distinct from the other genotypes. Bark thickness was not correlated with yield in the DD genotypes but was negatively correlated with yield in the other genotypes. These results will guide the development of hybrid poplar genotypes that are both disease resistant and high yielding for cultivation in the southeastern United States.     

Genotype and environment determine allocation to and costs of resistance in quaking aspen

Although genetic variability and resource availability both influence plant chemical composition, little is known about how these factors interact to modulate costs of resistance, expressed as negative correlations between growth and defense. We evaluated genotype × environment effects on foliar chemistry and growth of quaking aspen (Populus tremuloides) by growing multiple aspen genotypes under variable conditions of light and soil nutrient availability in a common garden. Foliage was analyzed for levels of nitrogen, phenolic glycosides and condensed tannins. Bioassays of leaf quality were conducted with fourth-stadium gypsy moth (Lymantria dispar) larvae. Results revealed strong effects of plant genotype, light availability and nutrient availability; the importance of each factor depended upon compound type. For example, tannin concentrations differed little among genotypes and across nutrient regimes under low light conditions, but markedly so under high light conditions. Phenolic glycoside concentrations, in contrast, were largely determined by genotype. Variation in phenolic glycoside concentrations among genotypes was the most important factor affecting gypsy moth performance. Gypsy moth biomass and development time were negatively and positively correlated, respectively, with phenolic glycoside levels. Allocation to phenolic glycosides appeared to be costly in terms of growth, but only under resource-limiting conditions. Context-dependent trade-offs help to explain why costs of allocation to resistance are often difficult to demonstrate.     

Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions

Key message

Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset.

Abstract

Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1 % on average and the variability in prediction accuracy decreased by 10.8 %. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.     

Genomic prediction applied to high-biomass sorghum for bioenergy production

The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesCπ, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.     

Fungal-Fungal Associations Affect the Assembly of Endophyte Communities in Maize (Zea mays)

Many factors can affect the assembly of communities, ranging from species pools to habitat effects to interspecific interactions. In microbial communities, the predominant focus has been on the well-touted ability of microbes to disperse and the environment acting as a selective filter to determine which species are present. In this study, we investigated the role of biotic interactions (e.g., competition, facilitation) in fungal endophyte community assembly by examining endophyte species co-occurrences within communities using null models. We used recombinant inbred lines (genotypes) of maize (Zea mays) to examine community assembly at multiple habitat levels, at the individual plant and host genotype levels. Both culture-dependent and culture-independent approaches were used to assess endophyte communities. Communities were analyzed using the complete fungal operational taxonomic unit (OTU) dataset or only the dominant (most abundant) OTUs in order to ascertain whether species co-occurrences were different for dominant members compared to when all members were included. In the culture-dependent approach, we found that for both datasets, OTUs co-occurred on maize genotypes more frequently than expected under the null model of random species co-occurrences. In the culture-independent approach, we found that OTUs negatively co-occurred at the individual plant level but were not significantly different from random at the genotype level for either the dominant or complete datasets. Our results showed that interspecific interactions can affect endophyte community assembly, but the effects can be complex and depend on host habitat level. To our knowledge, this is the first study to examine endophyte community assembly in the same host species at multiple habitat levels. Understanding the processes and mechanisms that shape microbial communities will provide important insights into microbial community structure and the maintenance of microbial biodiversity.     

Genotypic variations in carbon isotope discrimination, transpiration efficiency, and biomass production in rice as affected by soil water conditions and N

Genotypic and environmental (soil water regime and N level) variation in carbon isotope discrimination (CID) in relation to the gas exchange, transpiration efficiency (A/T), and biomass production were investigated in field experiments using eleven rice (Oryza sativa L.) genotypes. The results showed that genotype was more dominant for variation in CID than in total biomass. Genotypic ranking in CID was consistent across environments because of small genotype × environment interactions. Japonica genotypes tended to have lower CID than indica genotypes. Higher soil water and lower N rate significantly increased CID. Variation in CID was slightly smaller for water regime than for genotype. There was a negative correlation between CID andA/T among genotypes within water regimes. Genotypic variation in CID was associated mainly with variation in stomatal conductance under all soil water regimes and with photosynthetic capacity in late growth stages under aerobic soil conditions. The decrease in CID at higher N was probably due to lower stomatal conductance under aerobic soil conditions and to higher photosynthetic rates under submerged soil conditions. The correlation between biomass and CID was not clear in aerobic soil, whereas it was positive in submerged soil, which indicated that the significance of lower or higher CID for improving biomass productivity may differ under different soil water regimes. Overall, the results implied a possible use of CID as a selection criterion for genotypic improvement inA/T and productivity in rice.     

Phenological responses of upland rice grown along an altitudinal gradient

High altitude upland rice (Oryza sativa L.) production systems are expected to benefit from climate change induced increase in temperatures. The potential yield of rice genotypes is governed by the thermal environment experienced during crop development phases when yield components are determined. Thus, knowledge on genotypic variability in phenotypic responses to variable temperature is required for assessing the adaptability of rice production to changing climate. Although, several crop models are available for this task, genotypic thermal constants used to simulate crop phenology vary strongly among the models and are under debate. Therefore, we conducted field trials with ten contrasting upland rice (O. sativa L.) genotypes on three locations along an altitudinal gradient with five monthly staggered sowing dates for two years in Madagascar with the aim to study phenological responses at different temperature regimes. We found that, crop duration is equally influenced by genotype selection, sowing date and year in the high altitude. In contrast, in mid altitudes genotype has no effect on crop duration. At low altitudes crop duration is more affected by sowing date. Grain yield is strongly affected by low temperatures at high altitudes and severly influenced by frequent tropical cyclones at low altitudes. In high altitude, genotype explained 68% of variation in spikelet sterility, whereas in mid and low altitudes environment explained more than 70% of the variation. The phenological responses determining crop duration and yield, the basic genotypic thermal constants, and the analyses of genotypic thermal responses with regard to spikelet sterility reported here, provide valuable information for the improvement of rice phenological models urgently needed to develop new genotypes and better adapted cropping calendars.     

臭冷杉生物量分配格局及异速生长模型

摘 要：臭冷杉是长白山阔叶红松林中重要针叶树种,采用整株收获法分析21株臭冷杉地上地下生物量分配格局。在枝条水平上采用样枝直径（BD）、样枝长度（BL）、样枝所在轮生枝位置（WP）建立活枝、针叶生物量异速生长模型,在植株水平上采用胸径（DBH）、树高（H）、年龄（Age）、树冠长度（CL）、树冠比率（CR）、南北向冠幅（CW1）、东西向冠幅（CW2）等变量建立树干木质、树皮、活枝、针叶、粗根及整株生物量模型。并利用逐步线性回归法获得不同器官生物量最优模型。结果表明：（1）活枝生物量主要集中在树冠中下层,针叶生物量集中在树冠中层。树冠中层和下层枝叶生物量无显著差异（p>0.05）;（2）21株臭冷杉地上生物量和地下生物量变动范围分别为1.026–506.047 kg/株和0.241–112.000 kg/株。粗根、活枝、针叶、树干木质、树皮及枯枝生物量占整株生物量的相对比例分别为18.68%、18.39%、12.02%、39.29%、8.70%和2.92%;（3）地上生物量与地下生物量呈显著线性相关（p<0.001）,拟合线性方程斜率为0.23;（4）枝条水平上,活枝生物量模型解释量超过95%,平均预测误差小于30%。与单变量（BD）活枝生物量模型相比,2变量（BD、BL）和3变量（BD、BL、WP）模型解释量分别提高1.2%和2.0%,平均预测误差分别下降6.26%和9.27%。针叶生物量相对较难预测,模型解释量仅为82.7%,平均预测误差接近50%,模型中增加BL 和WP变量并未提高针叶生物量的预测精度。活枝生物量与BD、BL、WP正相关,针叶生物量与BD正相关,与BL、WP负相关;（5）植株水平上,基于胸径的单变量模型可解释量大于90%,增加树高变量未能显著提高生物量模型的预测精度。年龄决定了臭冷杉的树干生物量,忽视年龄变量将会产生生物量预测误差。树冠特征是影响枝叶生物量预测精度的重要变量。综合考虑模型的可解释量及回归系数显著性可知,胸径是预测臭冷杉不同器官生物量的可靠变量。