This work studied the effects of tree species composition on soil carbon storage in five mixed stands dominated by oriental beech and grown in the western Caspian region in Guilan province, called Astara, Asalem, Fuma...This work studied the effects of tree species composition on soil carbon storage in five mixed stands dominated by oriental beech and grown in the western Caspian region in Guilan province, called Astara, Asalem, Fuman, Chere and Shenrud. The thickness of the litter layer, soil characteristics, tree composition and percentage of canopy coverage were measured in each stand. Total soil organic carbon differed significantly by stand. Total （organic） carbon stores at Fuman, which had the lowest tree species richness with 2 species and least canopy coverage （75%）, were significantly （p〈0.05） higher than at other locations. Carbon stor-age in topsoil （0-10 cm） was significantly lower in Shenrud, which had the highest tree species richness with 5 species and highest canopy cov-erage （95%）. The high percentage of canopy coverage in Shenrud proba-bly limited the conversion of litter to humus. However, in the second soil layer （10-25 cm）, Asalem, with high tree species richness and canopy coverage, had the highest carbon storage. This can be explained by the different rooting patterns of different tree species. In the Hyrcanian forest. According to the results, it can be concluded that not only tree composi-tion but also canopy coverage percentage should be taken under consid-eration to manage soil carbon retention and release.展开更多
Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practi...Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data.Here,we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean(Glycine max(L.)Merr.)varieties to identify previously uncharacterized loci.Specifically,we focused on the dissection of canopy coverage(CC)variation from this rich data set.We also inferred the speed of canopy closure,an additional dimension of CC,from the time-series data,as it may represent an important trait for weed control.Genome-wide association studies(GWASs)identified 35 loci exhibiting dynamic associations with CC across developmental stages.The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci(QTLs)detected in previous studies of adult plants and the identification of novel QTLs influencing CC.These novel QTLs were disproportionately likely to act earlier in development,which may explain why they were missed in previous single-time-point studies.Moreover,this time-series data set contributed to the high accuracy of the GWASs,which we evaluated by permutation tests,as evidenced by the repeated identification of loci across multiple time points.Two novel loci showed evidence of adaptive selection during domestication,with different genotypes/haplotypes favored in different geographic regions.In summary,the time-series data,with soybean CC as an example,improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.展开更多
Climate change and urban heat islands are intensifying the frequency and severity of heatwaves,emphasizing the need for resilient and sustainable strategies to cool urban outdoor and indoor spaces.Urban trees are iden...Climate change and urban heat islands are intensifying the frequency and severity of heatwaves,emphasizing the need for resilient and sustainable strategies to cool urban outdoor and indoor spaces.Urban trees are identified as an effective solution,yet limited studies address how different tree deployment strategies enhance building thermal resilience against heatwaves.This study examines the impact of strategic urban tree deployment on building thermal resilience across a neighborhood in London,Canada.Two deployment strategies are assessed:a straightforward strategy based on outdoor temperature hotspots,and a more complex strategy based on building indoor heat stress.The analysis incorporates tree growth and its effect on canopy coverage.A coupled microclimate-building performance simulation evaluates outdoor and indoor thermal conditions,with thermal resilience quantified using a novel method integrating microclimate effects,heat stress intensity,and exposure duration.Results indicated that when canopy coverage increases from 6%to the Nature Canada-recommended 30%,both strategies achieve similar maximum reductions in building surrounding outdoor air temperature(4.0℃)and Standard Effective Temperature(6.9℃),as well as comparable reductions in indoor thermal stress.However,at lower canopy coverage levels(≤20%),the indoor based strategy achieves a more uniform resilience distribution and enhances thermal resilience for the majority of buildings with poorer baseline conditions.At 30%canopy coverage and above,the differences between the two strategies become less pronounced,making tree deployment based on outdoor temperature hotspots a straightforward yet effective strategy for improving neighborhood thermal resilience.展开更多
Forest stand structure is not only a crucial factor for regulating forest functioning but also an important indicator for sustainable forest management and ecosystem services.Although there exists a few national/globa...Forest stand structure is not only a crucial factor for regulating forest functioning but also an important indicator for sustainable forest management and ecosystem services.Although there exists a few national/global structure databases for natural forests,a country-wide synthetic structure database for plantation forests over China,the world’s largest player in plantation forests,has not been achieved.In this study,we built a country-wide synthetic stand structure database by surveying more than 600 peer-reviewed literature.The database covers tree species,mean stand age,mean tree height,stand density,canopy coverage,diameter at breast height,as well as the associated ancillary in-situ topographical and soil properties.A total of 594 pub-lished studies concerning diverse forest stand structure parameters were compiled for 46 tree species.This first synthesis for stand structure of plantation forests over China supports studies on the evolution/health of plantation forests in response to rapid climate change and intensified disturbances,and benefits country-wide sustainable forest management,future afforestation or reforestation planning.Potential users include those studying forest community dynamics,regional tree growth,ecosystem stability,and health,as well as those working with conservation and sustainable management.This dataset is freely acces-sible at http://www.doi.org/10.11922/sciencedb.j00076.00091.展开更多
Data-driven techniques could be used to enhance decision-making capacity of breeders and farmers.We used an RGB camera on an unmanned aerial vehicle(UAV)to collect time series data on sugar beet canopy coverage(CC)and...Data-driven techniques could be used to enhance decision-making capacity of breeders and farmers.We used an RGB camera on an unmanned aerial vehicle(UAV)to collect time series data on sugar beet canopy coverage(CC)and canopy height(CH)from small-plot breeding fields including 20 genotypes per season over 3 seasons.Digital orthomosaic and digital surface models were created from each flight and were converted to individual plot-level data.Plot-level data including CC and CH were calculated on a per-plot basis.A multiple regression model was fitted,which predicts root weight(RW)(r=0.89,0.89,and 0.92 in the 3 seasons,respectively)and sugar content(SC)(r=0.79,0.83,and 0.77 in the 3 seasons,respectively)using individual time point CC and CH data.Individual CC and CH values in late June tended to be strong predictors of RW and SC,suggesting that early season growth is critical for obtaining high RW and SC.Coefficient of parentage was not a strong factor influencing SC.Integrals of CC and CH time series data were calculated for genetic analysis purposes since they are more stable over multiple growing seasons.Calculations of general combining ability and specific combining ability in F1 offspring demonstrate how growth curve quantification can be used in diallel cross analysis and yield prediction.Our simple yet robust solution demonstrates how state-of-the-art remote sensing tools and basic analysis methods can be applied to small-plot breeder fields for selection purpose.展开更多
文摘This work studied the effects of tree species composition on soil carbon storage in five mixed stands dominated by oriental beech and grown in the western Caspian region in Guilan province, called Astara, Asalem, Fuman, Chere and Shenrud. The thickness of the litter layer, soil characteristics, tree composition and percentage of canopy coverage were measured in each stand. Total soil organic carbon differed significantly by stand. Total （organic） carbon stores at Fuman, which had the lowest tree species richness with 2 species and least canopy coverage （75%）, were significantly （p〈0.05） higher than at other locations. Carbon stor-age in topsoil （0-10 cm） was significantly lower in Shenrud, which had the highest tree species richness with 5 species and highest canopy cov-erage （95%）. The high percentage of canopy coverage in Shenrud proba-bly limited the conversion of litter to humus. However, in the second soil layer （10-25 cm）, Asalem, with high tree species richness and canopy coverage, had the highest carbon storage. This can be explained by the different rooting patterns of different tree species. In the Hyrcanian forest. According to the results, it can be concluded that not only tree composi-tion but also canopy coverage percentage should be taken under consid-eration to manage soil carbon retention and release.
基金partially supported by the National Key R&D Program of China (2021YFD1201601)the Agricultural Science and Technology Innovation Program (ASTIP)of the Chinese Academy of Agricultural Sciences (CAAS-ZDRW202109)+1 种基金Hainan Yazhou Bay Seed Lab (B21HJ0221)supported by the UK Biotechnology and Biological Sciences Research Council as part of the Designing Future Wheat Project (BB/P016855/1)。
文摘Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data.Here,we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean(Glycine max(L.)Merr.)varieties to identify previously uncharacterized loci.Specifically,we focused on the dissection of canopy coverage(CC)variation from this rich data set.We also inferred the speed of canopy closure,an additional dimension of CC,from the time-series data,as it may represent an important trait for weed control.Genome-wide association studies(GWASs)identified 35 loci exhibiting dynamic associations with CC across developmental stages.The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci(QTLs)detected in previous studies of adult plants and the identification of novel QTLs influencing CC.These novel QTLs were disproportionately likely to act earlier in development,which may explain why they were missed in previous single-time-point studies.Moreover,this time-series data set contributed to the high accuracy of the GWASs,which we evaluated by permutation tests,as evidenced by the repeated identification of loci across multiple time points.Two novel loci showed evidence of adaptive selection during domestication,with different genotypes/haplotypes favored in different geographic regions.In summary,the time-series data,with soybean CC as an example,improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.
基金funded by the National Research Council Canada(NRCC)through the seventh wave of its Postdoctoral Fellowship(PDF)program,and received support from Climate Resilient Built Environment Initiative(CRBE)of NRCCsupported by an NSERC DG grant to Prof.James Voogt。
文摘Climate change and urban heat islands are intensifying the frequency and severity of heatwaves,emphasizing the need for resilient and sustainable strategies to cool urban outdoor and indoor spaces.Urban trees are identified as an effective solution,yet limited studies address how different tree deployment strategies enhance building thermal resilience against heatwaves.This study examines the impact of strategic urban tree deployment on building thermal resilience across a neighborhood in London,Canada.Two deployment strategies are assessed:a straightforward strategy based on outdoor temperature hotspots,and a more complex strategy based on building indoor heat stress.The analysis incorporates tree growth and its effect on canopy coverage.A coupled microclimate-building performance simulation evaluates outdoor and indoor thermal conditions,with thermal resilience quantified using a novel method integrating microclimate effects,heat stress intensity,and exposure duration.Results indicated that when canopy coverage increases from 6%to the Nature Canada-recommended 30%,both strategies achieve similar maximum reductions in building surrounding outdoor air temperature(4.0℃)and Standard Effective Temperature(6.9℃),as well as comparable reductions in indoor thermal stress.However,at lower canopy coverage levels(≤20%),the indoor based strategy achieves a more uniform resilience distribution and enhances thermal resilience for the majority of buildings with poorer baseline conditions.At 30%canopy coverage and above,the differences between the two strategies become less pronounced,making tree deployment based on outdoor temperature hotspots a straightforward yet effective strategy for improving neighborhood thermal resilience.
基金This project was financially supported by the National Natural Science Foundation of China[No.41922001,41530747]the National Key Research and Development Program of China[No.2016YFD060020603]the Swedish Formas.
文摘Forest stand structure is not only a crucial factor for regulating forest functioning but also an important indicator for sustainable forest management and ecosystem services.Although there exists a few national/global structure databases for natural forests,a country-wide synthetic structure database for plantation forests over China,the world’s largest player in plantation forests,has not been achieved.In this study,we built a country-wide synthetic stand structure database by surveying more than 600 peer-reviewed literature.The database covers tree species,mean stand age,mean tree height,stand density,canopy coverage,diameter at breast height,as well as the associated ancillary in-situ topographical and soil properties.A total of 594 pub-lished studies concerning diverse forest stand structure parameters were compiled for 46 tree species.This first synthesis for stand structure of plantation forests over China supports studies on the evolution/health of plantation forests in response to rapid climate change and intensified disturbances,and benefits country-wide sustainable forest management,future afforestation or reforestation planning.Potential users include those studying forest community dynamics,regional tree growth,ecosystem stability,and health,as well as those working with conservation and sustainable management.This dataset is freely acces-sible at http://www.doi.org/10.11922/sciencedb.j00076.00091.
基金partially supported by CREST(JPMJCR1512)and the AIPAccelerationResearch(JPMJCR21U3)of JST.
文摘Data-driven techniques could be used to enhance decision-making capacity of breeders and farmers.We used an RGB camera on an unmanned aerial vehicle(UAV)to collect time series data on sugar beet canopy coverage(CC)and canopy height(CH)from small-plot breeding fields including 20 genotypes per season over 3 seasons.Digital orthomosaic and digital surface models were created from each flight and were converted to individual plot-level data.Plot-level data including CC and CH were calculated on a per-plot basis.A multiple regression model was fitted,which predicts root weight(RW)(r=0.89,0.89,and 0.92 in the 3 seasons,respectively)and sugar content(SC)(r=0.79,0.83,and 0.77 in the 3 seasons,respectively)using individual time point CC and CH data.Individual CC and CH values in late June tended to be strong predictors of RW and SC,suggesting that early season growth is critical for obtaining high RW and SC.Coefficient of parentage was not a strong factor influencing SC.Integrals of CC and CH time series data were calculated for genetic analysis purposes since they are more stable over multiple growing seasons.Calculations of general combining ability and specific combining ability in F1 offspring demonstrate how growth curve quantification can be used in diallel cross analysis and yield prediction.Our simple yet robust solution demonstrates how state-of-the-art remote sensing tools and basic analysis methods can be applied to small-plot breeder fields for selection purpose.
