Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi‐year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO₂ concentration [CO₂]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model‐based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well‐controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO₂] and temperature.     

A high‐throughput BAC end analysis protocol (BAC‐anchor) for profiling genome assembly and physical mapping

Traditional approaches for sequencing insertion ends of bacterial artificial chromosome (BAC) libraries are laborious and expensive, which are currently some of the bottlenecks limiting a better understanding of the genomic features of auto‐ or allopolyploid species. Here, we developed a highly efficient and low‐cost BAC end analysis protocol, named BAC‐anchor, to identify paired‐end reads containing large internal gaps. Our approach mainly focused on the identification of high‐throughput sequencing reads carrying restriction enzyme cutting sites and searching for large internal gaps based on the mapping locations of both ends of the reads. We sequenced and analysed eight libraries containing over 3 200 000 BAC end clones derived from the BAC library of the tetraploid potato cultivar C88 digested with two restriction enzymes, Cla I and Mlu I. About 25% of the BAC end reads carrying cutting sites generated a 60–100 kb internal gap in the potato DM reference genome, which was consistent with the mapping results of Sanger sequencing of the BAC end clones and indicated large differences between autotetraploid and haploid genotypes in potato. A total of 5341 Cla I‐ and 165 Mlu I‐derived unique reads were distributed on different chromosomes of the DM reference genome and could be used to establish a physical map of target regions and assemble the C88 genome. The reads that matched different chromosomes are especially significant for the further assembly of complex polyploid genomes. Our study provides an example of analysing high‐coverage BAC end libraries with low sequencing cost and is a resource for further genome sequencing studies.     

Genome sequence of M6, a diploid inbred clone of the high‐glycoalkaloid‐producing tuber‐bearing potato species Solanum chacoense,reveals residual heterozygosity

Cultivated potato (Solanum tuberosum L.) is a highly heterozygous autotetraploid that presents challenges in genome analyses and breeding. Wild potato species serve as a resource for the introgression of important agronomic traits into cultivated potato. One key species is Solanum chacoense and the diploid, inbred clone M6, which is self‐compatible and has desirable tuber market quality and disease resistance traits. Sequencing and assembly of the genome of the M6 clone of S. chacoense generated an assembly of 825 767 562 bp in 8260 scaffolds with an N50 scaffold size of 713 602 bp. Pseudomolecule construction anchored 508 Mb of the genome assembly into 12 chromosomes. Genome annotation yielded 49 124 high‐confidence gene models representing 37 740 genes. Comparative analyses of the M6 genome with six other Solanaceae species revealed a core set of 158 367 Solanaceae genes and 1897 genes unique to three potato species. Analysis of single nucleotide polymorphisms across the M6 genome revealed enhanced residual heterozygosity on chromosomes 4, 8 and 9 relative to the other chromosomes. Access to the M6 genome provides a resource for identification of key genes for important agronomic traits and aids in genome‐enabled development of inbred diploid potatoes with the potential to accelerate potato breeding.     

Timescale effects on the environmental control of carbon and water fluxes of an apple orchard

Model parameterization and validation of earth–atmosphere interactions are generally performed using a single timescale (e.g., nearly instantaneous, daily, and annual), although both delayed responses and hysteretic effects have been widely recognized. The lack of consideration of these effects hampers our capability to represent them in empirical‐ or process‐based models. Here we explore, using an apple orchard ecosystem in the North of Italy as a simplified case study, how the considered timescale impacts the relative importance of the single environmental variables in explaining observed net ecosystem exchange (NEE) and evapotranspiration (ET). Using 6 years of eddy covariance and meteorological information as input data, we found a decay of the relative importance of the modeling capability of photosynthetically active radiation in explaining both NEE and ET moving from half‐hourly to seasonal timescale and an increase in the relative importance of air temperature (T) and VPD. Satellite NDVI, used as proxy of leaf development, added little improvement to overall modeling capability. Increasing the timescale, the number of variables needed for parameterization decreased (from 5 to 1), while the proportion of variance explained by the model increased (r² from 0.56–0.78 to 0.85–0.90 for NEE and ET respectively). The wavelet coherence and the phase analyses showed that the two variables that increased their relative importance when the scale increased (T, VPD) were not in phase at the correlation peak of both ET and NEE. This phase shift in the time domain corresponds to a hysteretic response in the meteorological variables domain. This work confirms that the model parameterization should be performed using parameters calculated at the appropriate scale. It suggests that in managed ecosystems, where the interannual variability is minimized by the agronomic practices, the use of timescales large enough to include hysteretic and delayed responses reduces the number of required input variables and improves their explanatory capacity.     

Adaptation and plasticity in aboveground allometry variation of four pine species along environmental gradients

Plant species aboveground allometry can be viewed as a functional trait that reflects the evolutionary trade‐off between above‐ and belowground resources. In forest trees, allometry is related to productivity and resilience in different environments, and it is tightly connected with a compromise between efficiency‐safety and competitive ability. A better understanding on how this trait varies within and across species is critical to determine the potential of a species/population to perform along environmental gradients. We followed a hierarchical framework to assess tree height‐diameter allometry variation within and across four common European Pinus species. Tree height‐diameter allometry variation was a function of solely genetic components –approximated by either population effects or clinal geographic responses of the population's site of origin– and differential genetic plastic responses –approximated by the interaction between populations and two climatic variables of the growing sites (temperature and precipitation)–. Our results suggest that, at the species level, climate of the growing sites set the tree height‐diameter allometry of xeric and mesic species (Pinus halepensis, P. pinaster and P. nigra) apart from the boreal species (P. sylvestris), suggesting a weak signal of their phylogenies in the tree height‐diameter allometry variation. Moreover, accounting for interpopulation variability within species for the four pine species aided to: (1) detect genetic differences among populations in allometry variation, which in P. nigra and P. pinaster were linked to gene pools –genetic diversity measurements–; (2) reveal the presence of differential genetic variation in plastic responses along two climatic gradients in tree allometry variation. In P. sylvestris and P. nigra, genetic variation was the result of adaptive patterns to climate, while in P. pinaster and P. halepensis, this signal was either weaker or absent, respectively; and (3) detect local adaptation in the exponent of the tree height‐diameter allometry relationship in two of the four species (P. sylvestris and P. nigra), as it was a function of populations' latitude and altitude variables. Our findings suggest that the four species have been subjected to different historical and climatic constraints that might have driven their aboveground allometry and promoted different life strategies.     

Impact of agronomic uncertainty in biomass production and endogenous commodity prices on cellulosic biofuel feedstock composition

This study evaluates the effect of agronomic uncertainty on bioenergy crop production as well as endogenous commodity and biomass prices on the feedstock composition of cellulosic biofuels under a binding mandate in the United States. The county‐level simulation model focuses on both field crops (corn, soybean, and wheat) and biomass feedstocks (corn stover, wheat straw, switchgrass, and Miscanthus). In addition, pasture serves as a potential area for bioenergy crop production. The economic model is calibrated to 2022 in terms of yield, crop demand, and baseline prices and allocates land optimally among the alternative crops given the binding cellulosic biofuel mandate. The simulation scenarios differ in terms of bioenergy crop type (switchgrass and Miscanthus) and yield, biomass production inputs, and pasture availability. The cellulosic biofuel mandates range from 15 to 60 billion L. The results indicate that the 15 and 30 billion L mandates in the high production input scenarios for switchgrass and Miscanthus are covered entirely by agricultural residues. With the exception of the low production input for Miscanthus scenario, the share of agricultural residues is always over 50% for all other scenarios including the 60 billion L mandate. The largest proportion of agricultural land dedicated to either switchgrass or Miscanthus is found in the southern Plains and the southeast. Almost no bioenergy crops are grown in the Midwest across all scenarios. Changes in the prices for the three commodities are negligible for cellulosic ethanol mandates because most of the mandate is met with agricultural residues. The lessons learned are that (1) the share of agricultural residue in the feedstock mix is higher than previously estimated and (2) for a given mandate, the feedstock composition is relatively stable with the exception of one scenario.     

Ensemble projections elucidate effects of uncertainty in terrestrial nitrogen limitation on future carbon uptake

The magnitude of the nitrogen (N) limitation of terrestrial carbon (C) storage over the 21st century is highly uncertain because of the complex interactions between the terrestrial C and N cycles. We use an ensemble approach to quantify and attribute process‐level uncertainty in C‐cycle projections by analysing a 30‐member ensemble representing published alternative representations of key N cycle processes (stoichiometry, biological nitrogen fixation (BNF) and ecosystem N losses) within the framework of one terrestrial biosphere model. Despite large differences in the simulated present‐day N cycle, primarily affecting simulated productivity north of 40°N, ensemble members generally conform with global C‐cycle benchmarks for present‐day conditions. Ensemble projections for two representative concentration pathways (RCP 2.6 and RCP 8.5) show that the increase in land C storage due to CO₂ fertilization is reduced by 24 ± 15% due to N constraints, whereas terrestrial C losses associated with climate change are attenuated by 19 ± 20%. As a result, N cycling reduces projected land C uptake for the years 2006–2099 by 19% (37% decrease to 3% increase) for RCP 2.6, and by 21% (40% decrease to 9% increase) for RCP 8.5. Most of the ensemble spread results from uncertainty in temperate and boreal forests, and is dominated by uncertainty in BNF (10% decrease to 50% increase for RCP 2.6, 5% decrease to 100% increase for RCP 8.5). However, choices about the flexibility of ecosystem C:N ratios and processes controlling ecosystem N losses regionally also play important roles. The findings of this study demonstrate clearly the need for an ensemble approach to quantify likely future terrestrial C–N cycle trajectories. Present‐day C‐cycle observations only weakly constrain the future ensemble spread, highlighting the need for better observational constraints on large‐scale N cycling, and N cycle process responses to global change.     

Linkages of Farmers' Operations with Rhizoctonia Root Rot Spread in Bean Crops on a Regional Basis

The associations of Rhizoctonia root rot (RRR) with a number of agronomic and yield variables were characterized at different growth stages in 122 commercial bean fields in Zanjan, Iran. A lower RRR incidence was detected in red beans compared with white beans. RRR incidence was greater in drought‐exposed fields compared with drought‐free fields. RRR incidence was higher following frequent irrigations at 2‐ to 3‐day intervals than at 4‐ to 9‐day intervals. The highest RRR incidence was associated with the densest category of plant populations and with the deepest plantings at 10–22 cm. Beans grown following alfalfa, bean and maize had a lower disease than rotations with potato. RRR incidence was greater in fields that received 50–500 kg/ha of urea compared with nonfertilized fields. RRR‐affected fields were recognized with a closer irrigation, earlier and deeper planting, denser weed population and lower yields than RRR‐free fields. According to loadings for second principal component, planting density and depth, urea usage and weed density corresponded with RRR incidence. Findings extend our understanding of RRR epidemics in diverse bean cropping systems.     

Homoeostatic maintenance of nonstructural carbohydrates during the 2015–2016 El Niño drought across a tropical forest precipitation gradient

Nonstructural carbohydrates (NSCs) are essential for maintenance of plant metabolism and may be sensitive to short‐ and long‐term climatic variation. NSC variation in moist tropical forests has rarely been studied, so regulation of NSCs in these systems is poorly understood. We measured foliar and branch NSC content in 23 tree species at three sites located across a large precipitation gradient in Panama during the 2015–2016 El Niño to examine how short‐ and long‐term climatic variation impact carbohydrate dynamics. There was no significant difference in total NSCs as the drought progressed (leaf P = 0.32, branch P = 0.30) nor across the rainfall gradient (leaf P = 0.91, branch P = 0.96). Foliar soluble sugars decreased while starch increased over the duration of the dry period, suggesting greater partitioning of NSCs to storage than metabolism or transport as drought progressed. There was a large variation across species at all sites, but total foliar NSCs were positively correlated with leaf mass per area, whereas branch sugars were positively related to leaf temperature and negatively correlated with daily photosynthesis and wood density. The NSC homoeostasis across a wide range of conditions suggests that NSCs are an allocation priority in moist tropical forests.     

Estimating the Effect of Cropland to Prairie Conversion on Peak Storm Run-Off

Much of the original U.S. grassland has undergone conversion to cropland. During the last few years, large first‐ and second‐order watershed scale projects have begun to reconstruct the native tallgrass prairie cover and biodiversity. The effect on watershed hydrological budget is largely unknown, especially concerning storm run‐off. Curve number variability is used to estimate the uncertainty of peak run‐off following the change in cover, given rainfall recurrence and watershed size. The method involves three steps: (1) estimate the time‐of‐concentration for many similar sized watersheds in the region, (2) define the probability distribution for time‐of‐concentration, curve numbers, and watershed area, (3) with these data, generate input variables for a Monte Carlo analysis, which can then be used to predict the mean and confidence interval of peak run‐off. As an example, spatial and hydrological characteristics of first‐ and second‐order watersheds ranging from 2 to 50 km² in the Red River of the North basin provide a log normal probability distribution for time‐of‐concentration. Using the range of watershed area and a β probability distribution for curve number uncertainty, the analysis predicts the change in peak run‐off from an ensemble of watershed realizations that characterize cropland to grassland conversion. Results suggest that given five‐ and 25‐year, 24‐hour rainfall recurrence, average reduction in peak run‐off will range from 50 to 55% and 40 to 45%, respectively, for the basin. A large range of uncertainty at the 80% confidence interval, however, indicates that an accurate prediction requires analysis for specific watersheds.     

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low‐quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision‐making framework will result in better‐informed, more robust decisions.     

Growth dynamics of Potamogeton pectinatus L. in Lake Burullus,Egypt: a modelling approach

In this study, we used a macrophyte model to describe the growth production and the interaction between above‐ and below‐ground organs of Potamogeton pectinatus in Lake Burullus, Egypt. Above‐ and below‐ground biomass of P. pectinatus was sampled on a monthly basis from April to December 2011 at three sites of Lake Burullus. Shoots started to grow in April, reached the maximum biomass in September and then rapidly decreased in October when they moved into the senescence stage. Tubers biomass reduced in August due to the upward translocation to shoots, but sharply increased to the maximum in October by downward translocation from shoots and roots. Potamogeton pectinatus allocated approximately 82.3% of its total biomass to shoots, 15.5% to tubers and 2.2% to roots.     

Mangrove blue carbon stocks and dynamics are controlled by hydrogeomorphic settings and land‐use change

Globally, carbon‐rich mangrove forests are deforested and degraded due to land‐use and land‐cover change (LULCC). The impact of mangrove deforestation on carbon emissions has been reported on a global scale; however, uncertainty remains at subnational scales due to geographical variability and field data limitations. We present an assessment of blue carbon storage at five mangrove sites across West Papua Province, Indonesia, a region that supports 10% of the world's mangrove area. The sites are representative of contrasting hydrogeomorphic settings and also capture change over a 25‐years LULCC chronosequence. Field‐based assessments were conducted across 255 plots covering undisturbed and LULCC‐affected mangroves (0‐, 5‐, 10‐, 15‐ and 25‐year‐old post‐harvest or regenerating forests as well as 15‐year‐old aquaculture ponds). Undisturbed mangroves stored total ecosystem carbon stocks of 182–2,730 (mean ± SD: 1,087 ± 584) Mg C/ha, with the large variation driven by hydrogeomorphic settings. The highest carbon stocks were found in estuarine interior (EI) mangroves, followed by open coast interior, open coast fringe and EI forests. Forest harvesting did not significantly affect soil carbon stocks, despite an elevated dead wood density relative to undisturbed forests, but it did remove nearly all live biomass. Aquaculture conversion removed 60% of soil carbon stock and 85% of live biomass carbon stock, relative to reference sites. By contrast, mangroves left to regenerate for more than 25 years reached the same level of biomass carbon compared to undisturbed forests, with annual biomass accumulation rates of 3.6 ± 1.1 Mg C ha^?1 year^?1. This study shows that hydrogeomorphic setting controls natural dynamics of mangrove blue carbon stocks, while long‐term land‐use changes affect carbon loss and gain to a substantial degree. Therefore, current land‐based climate policies must incorporate landscape and land‐use characteristics, and their related carbon management consequences, for more effective emissions reduction targets and restoration outcomes.     

Costa Rican soils contain highly insecticidal granulovirus strains against Phthorimaea operculella and Tecia solanivora

The aim of this work was to isolate and characterize novel Phthorimaea operculella granulovirus (PhopGV) strains from Costa Rican soils. Three novel strains, named PhopGV‐CR3, PhopGV‐CR4 and PhopGV‐CR5, were isolated from three locations in Costa Rica, Alvarado, Zarcero and Abangares, respectively, by means of soaking potato tubers with diluted soil samples. An additional strain, PhopGV‐CR2, was identified from diseased larvae from a Tecia solanivora laboratory culture. Restriction fragment length polymorphisms obtained for each isolate with six restriction endonucleases (RENs) allowed their identification as four distinct PhopGV strains. Both REN and Polymerase chain reaction analyses indicated the existence of an array of genotypic variants present in all isolates. Bioassays in P. operculella and T. solanivora showed that PhopGV‐CR3 was well adapted to the two coexisting hosts with high levels of pathogenicity against both pest species. The mean lethal dose values of this strain were 2.8 OBs/mm² for P. operculella and less than 0.5 OBs/mm² for T. solanivora. We conclude that PhopGV‐CR3 shows great promise for soil application against these pests in Costa Rican potato crops.     

The Elongator complex‐associated protein DRL1 plays a positive role in immune responses against necrotrophic fungal pathogens in Arabidopsis

DEFORMED ROOT AND LEAVES1 (DRL1) is an Arabidopsis homologue of the yeast TOXIN TARGET4 (TOT4)/KILLER TOXIN‐INSENSITIVE12 (KTI12) protein that is physically associated with the RNA polymerase II‐interacting protein complex named Elongator. Mutations in DRL1 and Elongator lead to similar morphological and molecular phenotypes, suggesting that DRL1 and Elongator may functionally overlap in Arabidopsis. We have shown previously that Elongator plays an important role in both salicylic acid (SA)‐ and jasmonic acid (JA)/ethylene (ET)‐mediated defence responses. Here, we tested whether DRL1 also plays a similar role as Elongator in plant immune responses. Our results show that, although DRL1 partially contributes to SA‐induced cytotoxicity, it does not play a significant role in SA‐mediated expression of PATHOGENESIS‐RELATED genes and resistance to the virulent bacterial pathogen Pseudomonas syringae pv. maculicola ES4326. In contrast, DRL1 is required for JA/ET‐ and necrotrophic fungal pathogen Botrytis cinerea‐induced defence gene expression and for resistance to B. cinerea and Alternaria brassicicola. Furthermore, unlike the TOT4/KTI12 gene which, when overexpressed in yeast, confers zymocin resistance, a phenotype of the tot4/kti12 mutant, overexpression of DRL1 does not change B. cinerea‐induced defence gene expression and resistance to this pathogen. Finally, DRL1 contains an N‐terminal P‐loop and a C‐terminal calmodulin (CaM)‐binding domain and is a CaM‐binding protein. We demonstrate that both the P‐loop and the CaM‐binding domain are essential for the function of DRL1 in B. cinerea‐induced expression of PDF1.2 and ORA59, and in resistance to B. cinerea, suggesting that the function of DRL1 in plant immunity may be regulated by ATP/GTP and CaM binding.     

Dynamics of Myzus persicae arrestment by volatiles from Potato leafroll virus‐infected potato plants during disease progression

Green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), an important pest of potato (Solanum tuberosum L.) (Solanaceae), preferentially settles on Potato leafroll virus (PLRV)‐infected potato plants as compared with non‐infected ones, primarily in response to volatile organic compounds (VOCs) released by the plants. In this study, we examined the dynamics of these effects, measuring arrestment of apterous M. persicae in response to VOC from upper, middle, and lower leaflets of PLRV‐infected potato plants at the same stage in disease progression (4 weeks after inoculation), but inoculated at 1, 3, or 5 weeks after transplanting (WAT). Sham‐inoculated plants were used as controls and VOC were collected and quantified. Aphid arrestment was greater on PLRV‐infected plants inoculated at 1 and 3 WAT as compared with sham‐inoculated plants, but this preference was reversed in plants inoculated at 5 WAT. Relative arrestment of M. persicae by infected plants and VOC release was greater for lower and middle leaflets than for upper leaflets at 1 and 3 WAT compared to sham‐inoculated plants. The reverse was observed in plants inoculated at 5 WAT. Findings indicate that aphid preference is influenced by VOC release from PLRV‐ or sham‐inoculated potato plants and that VOC emissions and aphid preference depend upon the age at inoculation and leaf position within the potato plants. The implications of these dynamics in vector behavior for spread of PLRV in the field in natural and managed systems are discussed.     

Impaired sterol ester synthesis alters the response of Arabidopsis thaliana to Phytophthora infestans

Non‐host resistance of Arabidopsis thaliana against Phytophthora infestans, the causal agent of late blight disease of potato, depends on efficient extracellular pre‐ and post‐invasive resistance responses. Pre‐invasive resistance against P. infestans requires the myrosinase PEN2. To identify additional genes involved in non‐host resistance to P. infestans, a genetic screen was performed by re‐mutagenesis of pen2 plants. Fourteen independent mutants were isolated that displayed an enhanced response to Phytophthora (erp) phenotype. Upon inoculation with P. infestans, two mutants, pen2‐1 erp1‐3 and pen2‐1 erp1‐4, showed an enhanced rate of mesophyll cell death and produced excessive callose deposits in the mesophyll cell layer. ERP1 encodes a phospholipid:sterol acyltransferase (PSAT1) that catalyzes the formation of sterol esters. Consistent with this, the tested T‐DNA insertion lines of PSAT1 are phenocopies of erp1 plants. Sterol ester levels are highly reduced in all erp1/psat1 mutants, whereas sterol glycoside levels are increased twofold. Excessive callose deposition occurred independently of PMR4/GSL5 activity, a known pathogen‐inducible callose synthase. A similar formation of aberrant callose deposits was triggered by the inoculation of erp1 psat1 plants with powdery mildew. These results suggest a role for sterol conjugates in cell non‐autonomous defense responses against invasive filamentous pathogens.