In the subtropical highlands of Central Mexico, where the main crop is maize （Zea mays）, the conventional practice （CP） involves tillage, monoculture and residue removal, leading to soil degradation and unsustaina...In the subtropical highlands of Central Mexico, where the main crop is maize （Zea mays）, the conventional practice （CP） involves tillage, monoculture and residue removal, leading to soil degradation and unsustainable use of natural resources and agricultural inputs. Conservation agriculture （CA） has been proposed as a viable alternative in the region, based on reduction in tillage, retention of adequate levels of crop residues and soil surface cover and use of crop rotation. This study began in 2009 when the highlands of Central Mexico suffered from a prolonged drought during vegetative maize growth in July-August, providing an opportunity for the on-farm comparison of CA with CP under severe drought conditions which 21 climate change models projected to become more frequent. Under dry conditions, CA resulted in higher yields and net returns per hectare as early as the first and second years after adoption by farmers. As an average of 27 plots under farmers＇ management in 2009, the maize yields were 26% higher under CA （6.3 t ha-1） than under CP （5.0 t ha-l）. 2010 was close to a normal year in terms of rainfall so yields were higher than in 2009 for both practices; in addition, the yield difference between the practices was reduced to 19% （6.8 t ha-1 for CA vs. 5.7 t ha-1 for CP）. When all the 2009 and 2010 observations were analyzed in a modified stability analysis, CA had an overall positive effect of 3 838 Mexican Pesos ha-1 （320 $US ha-1） on net return and 1.3 t ha-1 on yield. After only one to two years of adoption by farmers on their fields, CA had higher yields and net returns under dry conditions that were even drier than those predicted by the analyzed 21 climate change models under a climate change scenario, emission scenario A2.展开更多
META-R(multi-environment trial analysis in R)is a suite of R scripts linked by a graphical user interface(GUI)designed in Java language.The objective of META-R is to accurately analyze multi-environment plant breeding...META-R(multi-environment trial analysis in R)is a suite of R scripts linked by a graphical user interface(GUI)designed in Java language.The objective of META-R is to accurately analyze multi-environment plant breeding trials(METs)by fitting mixed and fixed linear models from experimental designs such as the randomized complete block design(RCBD)and the alpha-lattice/lattice designs.META-R simultaneously estimates the best linear and unbiased estimators(BLUEs)and the best linear and unbiased predictors(BLUPs).Additionally,it computes the variance-covariance parameters,as well as some statistical and genetic parameters such as the least significant difference(LSD)at 5%significance,the coefficient of variation in percentage(CV),the genetic variance,and the broad-sense heritability.These parameters are very important in the selection of top performing genotypes in plant breeding.META-R also computes the phenotypic and genetic correlations among environments and between traits,as well as their statistical significance.The genetic correlations between environments or traits can be visualized in a biplot graph or a tree diagram(dendrogram).Genetic correlations are very important for identifying environments with similar behavior or making indirect selection and identifying the most highly associated traits.META-R performs multi-environment analyses by using the residual maximum likelihood(REML)method;these analyses can be done by environment,across environments by grouping factors(stress conditions,nitrogen content,etc.)and across environments;the analyses across environments can be done with a pre-defined degree of heritability.展开更多
In this paper,we study general recovery functions and treatment in the dynamics of an SIS model for sexually transmitted infections with nonzero partnership length.It is shown how partnership dynamics influences the p...In this paper,we study general recovery functions and treatment in the dynamics of an SIS model for sexually transmitted infections with nonzero partnership length.It is shown how partnership dynamics influences the predicted prevalence at the steady state and the basic reproduction number.Sobol's indices are used to evaluate the contribution of model parameters to the overall variance of R 0.The recovery functions studied here take into account that society's capacity to provide treatment is limited when the number of infected individuals is large.Bifurcation analysis is used to establish a relationship between an alert level of prevalence and the minimum recovery time that guarantees the eradication of the disease.We also show that a backward bifurcation can occur when there are delays in the treatment of infected individuals.展开更多
In this work we introduce two new Barzilai and Borwein-like steps sizes for the classical gradient method for strictly convex quadratic optimization problems.The proposed step sizes employ second-order information in ...In this work we introduce two new Barzilai and Borwein-like steps sizes for the classical gradient method for strictly convex quadratic optimization problems.The proposed step sizes employ second-order information in order to obtain faster gradient-type methods.Both step sizes are derived from two unconstrained optimization models that involve approximate information of the Hessian of the objective function.A convergence analysis of the proposed algorithm is provided.Some numerical experiments are performed in order to compare the efficiency and effectiveness of the proposed methods with similar methods in the literature.Experimentally,it is observed that our proposals accelerate the gradient method at nearly no extra computational cost,which makes our proposal a good alternative to solve large-scale problems.展开更多
Adaptation of ecosystems'root zones to climate change critically affects drought resilience and vegetation productivity.However,a global quantitative assessment of this mechanism is missing.In this study,we analyz...Adaptation of ecosystems'root zones to climate change critically affects drought resilience and vegetation productivity.However,a global quantitative assessment of this mechanism is missing.In this study,we analyzed high-quality observation-based data to find that the global average root zone water storage capacity(S_(R))increased by 11%,from 182 to 202 mm in 1982-2020.The total increase of Sr equals to 1652 billion m^(3) over the past four decades.S_(R) increased in 9 out of 12 land cover types,while three relatively dry types experienced decreasing trends,potentially suggesting the crossing of ecosystems'tipping points.Our results underscore the importance of accounting for root zone dynamics under climate changetoassessdroughtimpacts.展开更多
基金Supported by a scholarship from the Mexican National Science Commission(CONACYT)the CGIAR Research Program on Climate Change Agriculture and Food Security(CCAFS)the Mexican Secretariat of Agriculture,Livestock,Rural Development,Fisheries and Food(SAGARPA)
文摘In the subtropical highlands of Central Mexico, where the main crop is maize （Zea mays）, the conventional practice （CP） involves tillage, monoculture and residue removal, leading to soil degradation and unsustainable use of natural resources and agricultural inputs. Conservation agriculture （CA） has been proposed as a viable alternative in the region, based on reduction in tillage, retention of adequate levels of crop residues and soil surface cover and use of crop rotation. This study began in 2009 when the highlands of Central Mexico suffered from a prolonged drought during vegetative maize growth in July-August, providing an opportunity for the on-farm comparison of CA with CP under severe drought conditions which 21 climate change models projected to become more frequent. Under dry conditions, CA resulted in higher yields and net returns per hectare as early as the first and second years after adoption by farmers. As an average of 27 plots under farmers＇ management in 2009, the maize yields were 26% higher under CA （6.3 t ha-1） than under CP （5.0 t ha-l）. 2010 was close to a normal year in terms of rainfall so yields were higher than in 2009 for both practices; in addition, the yield difference between the practices was reduced to 19% （6.8 t ha-1 for CA vs. 5.7 t ha-1 for CP）. When all the 2009 and 2010 observations were analyzed in a modified stability analysis, CA had an overall positive effect of 3 838 Mexican Pesos ha-1 （320 $US ha-1） on net return and 1.3 t ha-1 on yield. After only one to two years of adoption by farmers on their fields, CA had higher yields and net returns under dry conditions that were even drier than those predicted by the analyzed 21 climate change models under a climate change scenario, emission scenario A2.
基金We are grateful for the financial support provided by the Bill&Melinda Gates Foundation and CIMMYT's CGIAR CRP(MAIZE and WHEAT),as well as the USAID Projects(Cornell University and Kansas State University)that generated the CIMMYT wheat data analyzed in this study.We acknowledge the financial support provided by the Foundation for Research Levy on Agricultural Products(FFL)and the Agricultural Agreement Research Fund(JA)in Norway through NFR grant 267806.
文摘META-R(multi-environment trial analysis in R)is a suite of R scripts linked by a graphical user interface(GUI)designed in Java language.The objective of META-R is to accurately analyze multi-environment plant breeding trials(METs)by fitting mixed and fixed linear models from experimental designs such as the randomized complete block design(RCBD)and the alpha-lattice/lattice designs.META-R simultaneously estimates the best linear and unbiased estimators(BLUEs)and the best linear and unbiased predictors(BLUPs).Additionally,it computes the variance-covariance parameters,as well as some statistical and genetic parameters such as the least significant difference(LSD)at 5%significance,the coefficient of variation in percentage(CV),the genetic variance,and the broad-sense heritability.These parameters are very important in the selection of top performing genotypes in plant breeding.META-R also computes the phenotypic and genetic correlations among environments and between traits,as well as their statistical significance.The genetic correlations between environments or traits can be visualized in a biplot graph or a tree diagram(dendrogram).Genetic correlations are very important for identifying environments with similar behavior or making indirect selection and identifying the most highly associated traits.META-R performs multi-environment analyses by using the residual maximum likelihood(REML)method;these analyses can be done by environment,across environments by grouping factors(stress conditions,nitrogen content,etc.)and across environments;the analyses across environments can be done with a pre-defined degree of heritability.
基金FS thanks Consejo Nacional de Ciencia y Tecnología(CONACyT)for the Graduate Fellowship Grant 331194.
文摘In this paper,we study general recovery functions and treatment in the dynamics of an SIS model for sexually transmitted infections with nonzero partnership length.It is shown how partnership dynamics influences the predicted prevalence at the steady state and the basic reproduction number.Sobol's indices are used to evaluate the contribution of model parameters to the overall variance of R 0.The recovery functions studied here take into account that society's capacity to provide treatment is limited when the number of infected individuals is large.Bifurcation analysis is used to establish a relationship between an alert level of prevalence and the minimum recovery time that guarantees the eradication of the disease.We also show that a backward bifurcation can occur when there are delays in the treatment of infected individuals.
基金supported in part by CONACYT(Mexico),Grants 258033,256126.
文摘In this work we introduce two new Barzilai and Borwein-like steps sizes for the classical gradient method for strictly convex quadratic optimization problems.The proposed step sizes employ second-order information in order to obtain faster gradient-type methods.Both step sizes are derived from two unconstrained optimization models that involve approximate information of the Hessian of the objective function.A convergence analysis of the proposed algorithm is provided.Some numerical experiments are performed in order to compare the efficiency and effectiveness of the proposed methods with similar methods in the literature.Experimentally,it is observed that our proposals accelerate the gradient method at nearly no extra computational cost,which makes our proposal a good alternative to solve large-scale problems.
基金supported by the National Key Research and Development Program of China(2024YFF0809304)National Natural Science Foundation of China(42071081)+2 种基金the European Research Council(ERC-2016-ADG-743080,Horizon Europe 101081661)Formas(2022-02089 and 2019-01220)the IKEA Foundation.
文摘Adaptation of ecosystems'root zones to climate change critically affects drought resilience and vegetation productivity.However,a global quantitative assessment of this mechanism is missing.In this study,we analyzed high-quality observation-based data to find that the global average root zone water storage capacity(S_(R))increased by 11%,from 182 to 202 mm in 1982-2020.The total increase of Sr equals to 1652 billion m^(3) over the past four decades.S_(R) increased in 9 out of 12 land cover types,while three relatively dry types experienced decreasing trends,potentially suggesting the crossing of ecosystems'tipping points.Our results underscore the importance of accounting for root zone dynamics under climate changetoassessdroughtimpacts.
