Successfully reported this slideshow.
Your SlideShare is downloading. ×

July 29-130-Matt Nowatzke

Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Loading in …3
×

Check these out next

1 of 29 Ad

More Related Content

Slideshows for you (20)

Similar to July 29-130-Matt Nowatzke (20)

Advertisement

More from Soil and Water Conservation Society (20)

Recently uploaded (20)

Advertisement

July 29-130-Matt Nowatzke

  1. 1. FORESITE An economic and environmental assessment tool for targeted agricultural change Matt Nowatzke mnowatz@iastate.edu
  2. 2. Photo: Flickr
  3. 3. Photo: Pix4Dfields
  4. 4. 14” 4.5” Photo: Iowa Public Radio
  5. 5. Heggenstaller et al. (2008)
  6. 6. SO WHAT CAN WE DO?
  7. 7. BUILD SOIL HEALTH PREVENT EROSION REDUCE NUTRIENT LOSS Photo: Conservation Media Library
  8. 8. Environmental Benefits Proportion of Landscape in Perennials Socioeconomic Benefits Schulte et al. (2006); Asbjornsen et al. (2014) 
  9. 9. 46% stable high yield 28% unstable yield 26% stable low yield Basso et al. (2019) Brandes et al. (2016)
  10. 10. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  11. 11. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  12. 12. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  13. 13. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  14. 14. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  15. 15. Spatial boundaries Soils data Weather data Financial Data Land Management Field-scale historical crop rotations Subfield soil types Subfield soil yield estimates Economic data layers APSIM crop model Environmental outputs User- defined Inputs Statistical emulator
  16. 16. WHAT DOES FORESITE OFFER?
  17. 17. FORESITE YIELD NO3 LEACHING SOC CHANGE Statistical emulator
  18. 18. https://www.webtekcc.com/blog/development/decrease- website-load-time
  19. 19. FORESITE WEPP 3 4 YIELD NO3 LEACHING SOC CHANGE EROSION ??????? Statistical emulator
  20. 20. Harry Potter and the Goblet of Fire
  21. 21. Photos: Conservation Media Library
  22. 22. RESEARCHERS POLICY MAKERS EXTENSION LAND OWNERS/OPERATORS
  23. 23. https://www.hotfootdesign.co.uk/ white-space/bad-door-design/
  24. 24. Photo: Reddit u/AccidentalFloridaMan
  25. 25. https://medium.theuxblog.com/user-testing-v-s-usability-testing-c3a9edd04612
  26. 26. Photo: Pix4Dfields
  27. 27. Photo: Conservation Media Library
  28. 28. THANK YOU Matt Nowatzke mnowatz@iastate.edu

Editor's Notes

  • Again, my name is Matt Nowatzke, and today I’m going to talk about Foresite, a project underneath the new C-CHANGE initiative, an interdisciplinary research initiative aimed at getting more variety into the agricultural landscape, and Foresite is meant to target areas of unprofitable land for land-use change. So why do we need land-use change?
  • Here is an image of the hypoxic dead zone in the Gulf of Mexico which I’m sure many of you are familiar with. For 2019 the dead zone is predicted to be the size of Massachusetts due to the high spring rainfall this year and excess nutrient loss. The majority of this nutrient pollution comes from agriculture in the Upper Mississippi River Basin.
  • While there are many states contributing to the Gulph Hypoxia, I’m going to talk a lot about Iowa today. A lot of the problems with pollution in the Gulph of Mexico is land use change, and Iowa is a prime example of where change is most needed. About 80% of all land is agricultural and 90% of that agricultural land is in a two-crop, monoculture, annual system. Here we can see after an Iowa spring flood with what we call ‘prairie potholes’. These are areas of flat, low-lying land that you could occassionally canoe down, and something that is becoming more of a regular occurrence each year.
  • But nutrient loss isn’t the only problem in Iowa. The picture here is of the rest area near Adair IA on Interstate 80. If we look at the left side of the picture at the tallest pillar, this shows how in 1850 Iowa had on average 14” of topsoil, and if look at the right most pillar, in 2000 Iowa had an average of 4.5” of topsoil. That’s about 70% of topsoil lost in 150 years, and lucky for Iowa it had so much topsoil to begin with.
  • This is 2008 to 2018 hillslope soil loss from the Daily Erosion Project, a collaboration between ISU and the Iowa Water Center – please check out their booth and say hello – As we’re watching the video on the right we have tons of hillslope soil loss per acre and each little area on the map is a HUC 12 watershed. You can see high areas of erosion in western and eastern Iowa where it’s quite hilly, but still in Central Iowa where it’s flat we can see areas with 1-3 tons/acre of soil loss in just a decade.
  • Land-use problem --- Erosion in winter, leaching and erosion in spring when soil is bare.
  • Okay, so we know the problem but now what can we do about it? What land-use changes could we make? How do we get other crops into the system?
  • If annual cropping systems are problematic, why don’t we look to perennials? Research shows that perennial plants in general will build soil health, prevent erosion, and reduce nutrient loss. Okay, but converting all of our land to perennials like prairie, biomass energy crops, or even new perennial grains would be a) pretty challenging and b) probably pretty detrimental to the economy.
  • This is where the hypothesis of disproportionate benefits comes in, where if we put a relatively low amount of perennials into land use at strategic locations ***SMILEY FACE CLICK*** we can have exponentially larger environmental and socioeconomic benefits in relation to the amount of land taken out of production. Now, at the reception yesterday I believe one of the speakers mentioned Pennsylvania is 70% forest, so this does not apply to landscapes such as Pennsylvania; good job Pennsylvanians.
  • So where should we put perennials? Brandes et al looked at sub-field profitability retrospectively in Iowa over four years and found large agricultural areas of production that were actually losing money or breaking even between 2010 and 2013. More recently, Basso et al looked at 10 agricultural states and found 46% of land to have a stable high yield, 28% to have unstable yield, and 26% to have consistently low yields. This means that potentially over 50% of cropland in a given year isn’t performing.
  • So we created Foresite as a way to target marginal areas for land-use change.
  • -----* Pause *----- The best question. This concept is not new, so how is Foresite different from other precision ag conservation tools already out there?
  • Well, here we have the current basic function that Foresite can do: it uses data and the APSIM crop model to output yield and some environmental outputs. This is novel on its own in that a lot of other precision models compute profitability using NASS county yield averages, CSR2 ratings, or a combination of the two, but with APSIM we can simulate yields based on individual field soils, management, and weather. But, one of the coolest parts about Foresite is the use of this statistical emulator. So using the emulator we aren’t actually running APSIM anymore, we’re using machine learning aka statistics to predict new output based on simulations we’ve already done before. So we’re taking thousands, or hundreds of thousands, of previously run APSIM output that’s been saved to a database, and we use this emulator to make predictions with new data without having to run the APSIM model again. This is important in two major ways. If we tried to run the crop model a hundred thousand times we’d get this **** GO TO NEXT SLIDE***
  • With the emulator we’re not running a hundred thousand, but finding similar output to our new input, decreasing compute time drastically. *** GO TO NEXT SLIDE***
  • And 2, again we’re no longer running APSIM really, so we’re no longer limited by one model. We can also run other models and ake their output to run new simulations ---- like the Water Erosion Prediction Project or WEPP, so now we can do erosion in Foresite. And we can take a third model or a fourth model, you get the idea. Yes, the same thing went through my mind when I started working with statistical emulators *** NEXT SLIDE ****
  • Before we start to add additional models though, right now though we can only do an analysis of what it looks like with a corn/soy and continuous corn rotation, so near-future steps are to get prairie, pasture, and cover crops into the APSIM model next so we can start looking at alternative land-use scenarios and how that affects both economics and environmental outcomes.
  • So who do we see using Foresite? The ultimate goal of Foresite, beyond advancing science, is to create an open-source web-mapping tool that’s out there for anyone to use, including fellow researchers, policy makers, and land owners/operators.
  • Before that though, can I get a quick show of hands. Who here has ever gone to pull open a door to only realize you were supposed to push? Or vice verse went to push and instead needed to pull?
  • And who here has ever turned on the wrong burner on your stovetop to your misfortune?
  • C-CHANGE, the umbrella research group that Foresite is under, is an interdisciplinary group of agronomists, sociologists, engineers, and communications specialist. I myself, though I grew up on a working farm, my training until recently was not in agronomy but in human-computer interaction. And what that means is before we make anything we need to first talk to the groups of people previously mentioned to see how this can fit their needs, and once we decide how we want to approach our web-mapping tool we then need to test what we’ve made throughout the build process to ensure it’s user-friendly.
  • And it’s our goal that by taking this interdisciplinary, magical approach, we can work towards turning this:
  • Into something like this

×