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Blesh, Jennifer
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- Creator:
- Surdoval, Alison, Jain, Meha, Wang, Haoyu, and Blesh, Jennifer
- Description:
- We conducted a mixed-methods study to understand how financial incentive programs impact transitions to cover cropping in Michigan. Michigan farms span a wide range of soil types, climate conditions, and cropping systems that create opportunities for cover crop adoption in the state. We tested the relationship between Environmental Quality Incentives Program (EQIP) payments for cover crops and cover crop adoption between 2008-2019, as measured by remote sensing. Panel fixed effects regressions showed that EQIP increased winter cover crop presence. Every EQIP dollar for cover crops was associated with a 0.01 hectare increase in winter cover, while each hectare enrolled in an EQIP contract for cover crops was associated with a 0.86 – 0.93 hectare increase in winter cover.
- Keyword:
- adoption, cover crop, Environmental Quality Incentives Program, financial incentive program, Michigan, remote sensing
- Citation to related publication:
- Surdoval, A., Jain, M., Blair, E., Wang, H., and J. Blesh. In press. Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges.
- Discipline:
- Science
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- Creator:
- Bressler, Alison and Blesh, Jennifer
- Description:
- This dataset contains three data files and three corresponding metadata files used in Bressler, A., and J. Blesh. 2023. A grass-legume cover crop maintains nitrogen inputs and nitrous oxide fluxes from an organic agroecosystem. Ecosphere. The file “N2O_Flux.xls” contains daily nitrous oxide data organized by replicate block, treatment, and date. The file “Soil_N.xls” contains nitrate and ammonium data organized by replicate block, treatment, and date. The file “Cover_crop_corn_soil.xls” contains baseline soil fertility characteristics, cover crop and corn biomass, nitrogen and carbon content, legume BNF, and cumulative N2O content organized by replicate block and treatment. The corresponding metadata files: “N2O_Flux_metadata.xls”, “Soil_N_metadata.xls”, and “Cover_crop_corn_soil_metadata.xls” provide detailed descriptions of all variables in each data set and any abbreviations used.
- Keyword:
- cover crops, nitrous oxide, corn, biological nitrogen fixation, and legume-grass mixtures
- Citation to related publication:
- Bressler, A., and J. Blesh. 2023. A grass-legume cover crop maintains nitrogen inputs and nitrous oxide fluxes from an organic agroecosystem. Ecosphere. 14(2): e4428. https://doi.org/10.1002/ecs2.4428
- Discipline:
- Science
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- Creator:
- Bressler, Alison and Blesh, Jennifer
- Description:
- This dataset contains three data files and three corresponding metadata files used in Bressler, A., and J. Blesh. 2022. Episodic N2O emissions following tillage of a legume-grass cover crop mixture. Biogeosciences. The file “Cover_crop_soil_N2O.xls” contains data organized by site, replicate block, and treatment for spring cover crop biomass, nitrogen and carbon content, and legume BNF; soil fertility characteristics including potentially mineralizable nitrogen, particulate organic matter stocks, concentrations, and nitrogen content; and cumulative nitrous oxide data. The file “Soil_properties.xls” contains baseline soil data organized by site and replicate block. The file “Daily_N2O.xls” contains daily nitrous oxide data organized by site, replicate block, treatment, and date. The corresponding metadata files: “Cover_crop_soil_N2O_metadata.xls”, and “Soil_properties_metadata.xls”, and “Daily_N2O_metadata.xls” provided detailed descriptions of all variables in each data set and any abbreviations used.
- Keyword:
- cover crops, legume-grass mixtures, nitrous oxide, particulate organic matter, soil organic matter.
- Citation to related publication:
- Bressler, A., and J. Blesh. 2022. Episodic N2O emissions following tillage of a legume-grass cover crop mixture. Biogeosciences.
- Discipline:
- Science
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- Creator:
- Blesh, Jennifer and King, Alison E.
- Description:
- This dataset contains three data files used in: King, A.E. and J. Blesh, 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecological Applications. There are also three corresponding metadata files. The file “CRMA 2017 Main.csv” contains data for the control and treatment rotations used to construct pairwise comparisons for meta-analysis, response ratios calculated for soil organic carbon concentration, and change in carbon input. The dataset also includes management, soil, and other environmental characteristics for each site. The file “CRMA 2017 Diversity x Nitrogen.csv” contains data used to test whether N fertilizer inputs mediated the effect of functional diversity on SOC concentrations. The file “CRMA Annual grain.csv” contains data used to test for effects of crop rotation species diversity (one vs. two species, or two vs. three species) on SOC concentrations and C input (i.e., for the “grain-only” rotations). The dataset also includes management, soil, and other environmental characteristics for each site. The corresponding metadata files: “CRMA 2017 Main_metadata.csv”, “CRMA 2017 Diversity x Nitrogen_metadata.csv”, and “CRMA Annual grain _metadata.csv” provide a detailed description of all variables in each dataset. Note: On Jan 12, 2018 the following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- soil carbon, functional diversity, meta-analysis, cropping system, and student-friendly
- Citation to related publication:
- King, A. E. and Blesh, J. (2018), Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecol Appl, 28: 249–261. https://doi.org/10.1002/eap.1648
- Discipline:
- Science
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- Creator:
- Blesh, Jennifer
- Description:
- This dataset contains three data files used in: Blesh, J. 2017. Functional traits in cover crop mixtures: biological nitrogen fixation and multifunctionality. Journal of Applied Ecology. There are also three corresponding metadata files. The file “Ecosystem_functions_soil_species.csv” contains data organized by farm, treatment, replicate block, and species combining the fall and spring sampling time points. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation for the plant species. The dataset also includes measured soil characteristics for each farm site. The file “Ecosystem_functions_soil_treatment.csv” contains data organized by farm, treatment, and replicate block for the fall and spring sampling time points combined. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation aggregated by treatment. The dataset also includes measured soil characteristics for each farm site. The file “Traits_unstandardized.csv” contains individual plant trait data, a subset of which were used to calculate an index of functional diversity after they were standardized to have zero mean and unit variance. These data are organized by farm, treatment, replicate block, and species. The corresponding metadata files: “Ecosystem_functions_soil_species_metadata.csv”, “Ecosystem_functions_soil_treatment_metadata.csv”, and “Traits_unstandardized_metadata.csv” provide a detailed description of all variables in each dataset and any abbreviations used. Note: On Dec 19th 2017, the format of the files was changed to csv to aid preservation. The following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- agroecology, biological nitrogen fixation, functional diversity, and cover crop
- Citation to related publication:
- Blesh J. Functional traits in cover crop mixtures: Biological nitrogen fixation and multifunctionality. J Appl Ecol. 2018;55:38–48. https://doi.org/10.1111/1365-2664.13011
- Discipline:
- Science