| 1. |
- Han, Xue-Min, et al.
(författare)
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Evolution and Function of the Populus SABATH Family Reveal That a Single Amino Acid Change Results in a Substrate Switch
- 2018
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Ingår i: Plant and Cell Physiology. - : Oxford University Press. - 0032-0781 .- 1471-9053. ; 59:2, s. 392-403
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Tidskriftsartikel (refereegranskat)abstract
- Evolutionary mechanisms of substrate specificities of enzyme families remain poorly understood. Plant SABATH methyltransferases catalyze methylation of the carboxyl group of various low molecular weight metabolites. Investigation of the functional diversification of the SABATH family in plants could shed light on the evolution of substrate specificities in this enzyme family. Previous studies identified 28 SABATH genes from the Populus trichocarpa genome. In this study, we re-annotated the Populus SABATH gene family, and performed molecular evolution, gene expression and biochemical analyses of this large gene family. Twenty-eight Populus SABATH genes were divided into three classes with distinct divergences in their gene structure, expression responses to abiotic stressors and enzymatic properties of encoded proteins. Populus class I SABATH proteins converted IAA to methyl-IAA, class II SABATH proteins converted benzoic acid (BA) and salicylic acid (SA) to methyl-BA and methyl-SA, while class III SABATH proteins converted farnesoic acid (FA) to methyl-FA. For Populus class II SABATH proteins, both forward and reverse mutagenesis studies showed that a single amino acid switch between PtSABATH4 and PtSABATH24 resulted in substrate switch. Our findings provide new insights into the evolution of substrate specificities of enzyme families.
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| 2. |
- Muleke, Albert, et al.
(författare)
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Sustainable intensification with irrigation raises farm profit despite climate emergency
- 2023
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Ingår i: Plants, People, Planet. - : Wiley. - 2572-2611. ; 5:3, s. 368-385
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Tidskriftsartikel (refereegranskat)abstract
- Societal Impact StatementDespite comprising a small proportion of global agricultural land use, irrigated agriculture is enormously important to the global agricultural economy. Burgeoning food demand driven by population growth—together with reduced food supply caused by the climate crisis—is polarising the existing tension between water used for agricultural production versus that required for environmental conservation. We show that sustainable intensification via more diverse crop rotations, more efficient water application infrastructure and greater farm area under irrigation is conducive to greater farm business profitability under future climates.SummaryResearch aimed at improving crop productivity often does not account for the complexity of real farms underpinned by land-use changes in space and time.Here, we demonstrate how a new framework—WaterCan Profit—can be used to elicit such complexity using an irrigated case study farm with four whole-farm adaptation scenarios (Baseline, Diversified, Intensified and Simplified) with four types of irrigated infrastructure (Gravity, Pipe & Riser, Pivot and Drip).Without adaptation, the climate crisis detrimentally impacted on farm profitability due to the combination of increased evaporative demand and increased drought frequency. Whole-farm intensification—via greater irrigated land use, incorporation of rice, cotton and maize and increased nitrogen fertiliser application—was the only adaptation capable of raising farm productivity under future climates. Diversification through incorporation of grain legumes into crop rotations significantly improved profitability under historical climates; however, profitability of this adaptation declined under future climates. Simplified systems reduced economic risk but also had lower long-term economic returns.We conclude with four key insights: (1) When assessing whole-farm profit, metrics matter: Diversified systems generally had higher profitability than Intensified systems per unit water, but not per unit land area; (2) gravity-based irrigation infrastructure required the most water, followed by sprinkler systems, whereas Drip irrigation used the least water; (3) whole-farm agronomic adaptation through management and crop genotype had greater impact on productivity compared with changes in irrigation infrastructure; and (4) only whole-farm intensification was able to raise profitability under future climates.
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| 3. |
- Saarela, Svetlana, et al.
(författare)
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Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation
- 2022
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Ingår i: Remote Sensing of Environment. - : Elsevier. - 0034-4257 .- 1879-0704. ; 278
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Tidskriftsartikel (refereegranskat)abstract
- NASA's Global Ecosystem Dynamics Investigation (GEDI) mission offers data for temperate and pan-tropical estimates of aboveground forest biomass (AGB). The spaceborne, full-waveform LiDAR from GEDI provides sample footprints of canopy structure, expected to cover about 4% of the land area following two years of operation. Several options are available for estimating AGB at different geographical scales. Using GEDI sample data alone, gridded biomass predictions are based on hybrid inference which correctly propagates errors due to the modeling and accounts for sampling variability, but this method requires at least two GEDI tracks in the area of interest. However, there are significant gaps in GEDI coverage and in some areas of interest GEDI data may need to be combined with other wall-to-wall remotely sensed (RS) data, such as those from multispectral or SAR sensors. In these cases, we may employ hierarchical model-based (HMB) inference that correctly considers the additional model errors that result from relating GEDI data to the wall-to-wall data. Where predictions are possible from both hybrid and HMB inference the question arises which framework to choose, and under what circumstances? In this paper, we make progress towards answering these questions by comparing the performance of the two prediction frameworks under conditions relevant for the GEDI mission. Conventional model-based (MB) inference with wall-to-wall TanDEM-X data was applied as a baseline prediction framework, which does not involve GEDI data at all. An important feature of the study was the comparison of AGB predictors in terms of both standard deviation (SD: the square root of variance) and root mean square error (RMSE: the square root of mean square error – MSE). Since, in model-based inference, the true AGB in an area of interest is a random variable, comparisons of the performance of prediction frameworks should preferably be made in terms of their RMSEs. However, in practice only the SD can be estimated based on empirical survey data, and thus it is important also to study whether or not the difference between the two uncertainty measures is small or large under conditions relevant for the GEDI mission. Our main findings were that: (i) hybrid and HMB prediction typically resulted in smaller RMSEs than conventional MB prediction although the difference between the three frameworks in terms of SD often was small; (ii) in most cases the difference between hybrid and HMB inference was small in terms of both RMSE and SD; (iii) the RMSEs for all frameworks was substantially larger than the SDs in small study areas whereas the two uncertainty measures were similar in large study areas, and; (iv) spatial autocorrelation of model residual errors had a large effect on the RMSEs of AGB predictors, especially in small study areas. We conclude that hybrid inference is suitable in most GEDI applications for AGB assessment, due to its simplicity compared to HMB inference. However, where GEDI data are sparse HMB inference should be preferred.
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| 4. |
- Yang, Qi, et al.
(författare)
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Two dominant boreal conifers use contrasting mechanisms to reactivate photosynthesis in the spring
- 2020
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Boreal forests are dominated by evergreen conifers that show strongly regulated seasonal photosynthetic activity. Understanding the mechanisms behind seasonal modulation of photosynthesis is crucial for predicting how these forests will respond to changes in seasonal patterns and how this will affect their role in the terrestrial carbon cycle. We demonstrate that the two co-occurring dominant boreal conifers, Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies), use contrasting mechanisms to reactivate photosynthesis in the spring. Scots pine downregulates its capacity for CO2 assimilation during winter and activates alternative electron sinks through accumulation of PGR5 and PGRL1 during early spring until the capacity for CO2 assimilation is recovered. In contrast, Norway spruce lacks this ability to actively switch between different electron sinks over the year and as a consequence suffers severe photooxidative damage during the critical spring period.
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