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Tropical forests in a changing world: Investigating global change impacts in Amazonia and Puerto Rico

Talk in the weekly seminar series for Dept. of Environmental Science, Policy, and Mgmt. (ESPM) at the University of California, Berkeley

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Tropical forests in a changing world: Investigating global change impacts in Amazonia and Puerto Rico

  1. 1. Tropical forests in a changing world: Investigating global change impacts in Amazonia and Puerto Rico Christine S. O’Connell University of California, Berkeley Environmental Science, Policy, & Management(ESPM) Seminar Feb 25, 2016
  2. 2. Tropical forests and global change How is forest biogeochemistry affected by land use and climate change in two tropical sites? - Agriculture, energy and biogeochemistry in Amazonia - Drought, oxygen and biogeochemistry in Puerto Rico
  3. 3. Foley et al. (2011) Agriculture occupies ~38% of Earth’s terrestrial surface
  4. 4. Agricultural expansion and trade forces subsequently drive deforestation Hansen et al. (2013) (fig), Lenzen et al. (2012), Lambin et al. (2003), DeFries et al. (2010) Both
  5. 5. IPCC AR5 (2014) Remaining forests will likely experience changes to precipitation timing and amount
  6. 6. Land and climate are changing with poorly known consequences for tropical forest biogeochemistry
  7. 7. Tropical forests and global change Agriculture, energy and biogeochemistry in Amazonia - Extensification - Intensification
  8. 8. Saatchi et al. (2011), Brienen et al. (2012) Amazonia is the globe’s largest tract of tropical forest, contains 100 Gt of carbon in biomass, and rapidly cycles water
  9. 9. Nepstad et al. (2014) Deforestation (~20%) has been falling since 2004, as intensification on agricultural lands rises.
  10. 10. Q How does agricultural extensification impact carbon, energy and habitat? Can we balance these ecosystem services across space?
  11. 11. We combined data from remote sensing, model output, and geostatistical datasets to assess spatial variation in services
  12. 12. We combined data from remote sensing, model output, and geostatistical datasets to assess spatial variation in services • Changes in carbon (C) stocks • Energy balance regulation • Habitat quality
  13. 13. We combined data from remote sensing, model output, and geostatistical datasets to assess spatial variation in services • Changes in carbon (C) stocks • Energy balance regulation • Habitat quality We hypothesized that comparing these impacts to agricultural gains from expansion would lead to different conservation implications for each environmental goal.
  14. 14. C stock reductions relate to precipitation, landscape degradation, and soils Net aboveground biomass and mineral soil C lost after land use change
  15. 15. Local atmospheric drying after land use change is greater in the strongly seasonal east Reduction in exported moisture per day (via evapotranspiration)
  16. 16. …and local warming is higher in the same area Increase in local atmospheric temperature (annual average)
  17. 17. Plants, birds and mammals all have the highest relative species diversity in the Andes Amazon Number of species ranges represented in each grid cell
  18. 18. Tradeoffs consider both gains and losses Calories gained / change in ecosystem property
  19. 19. Ecosystem services: potential cobenefits
  20. 20. Ecosystem services: potential cobenefits
  21. 21. Ecosystem services: potential cobenefits
  22. 22. The location of future agricultural expansion will largely dictate the impacts of Amazonian land use on ecosystem services
  23. 23. Doubling Amazonia's agricultural lands at least harm to the environment We ran an algorithm that expands agriculture at the least combined “harm,” while changing the priority between C, energy balance and habitat Carbon storage priority level Carbon storage priority level Carbon storage priority level TgCEmitted SpeciesRangesAffected RegionalClimateIndex
  24. 24. Doubling Amazonia's agricultural lands at least harm to the environment We ran an algorithm that expands agriculture at the least combined “harm,” while changing the priority between C, energy balance and habitat Carbon storage priority level Carbon storage priority level Carbon storage priority level TgCEmitted SpeciesRangesAffected RegionalClimateIndex
  25. 25. Doubling Amazonia's agricultural lands at least harm to the environment Carbon storage priority level Carbon storage priority level Carbon storage priority level TgCEmitted SpeciesRangesAffected RegionalClimateIndex We ran an algorithm that expands agriculture at the least combined “harm,” while changing the priority between C, energy balance and habitat
  26. 26. Where matters: balancing ecosystem services in the tropics may require tradeoffs between environmental goals
  27. 27. Tropical forests and global change Agriculture, energy and biogeochemistry in Amazonia - Extensification - Intensification
  28. 28. Tanguro Ranch
  29. 29. Tanguro Ranch: Land use change impacts case study
  30. 30. Tanguro Ranch: Land use change impacts case study
  31. 31. Tanguro Ranch: Land use change impacts case study
  32. 32. Tanguro Ranch: Land use change impacts case study
  33. 33. Tanguro Ranch: Land use change impacts case study
  34. 34. Tanguro Ranch: Land use change impacts case study
  35. 35. Tanguro Ranch: Land use change impacts case study
  36. 36. Tanguro Ranch has three land uses: transitional Amazon forest (F), soybean cultivation (S), and soybean/maize (double cropped) cultivation (M). MAT: 27°C MAP: 1800 mm/y Management: N- (x2, M only) and P-fertilizer (x2), lime, pesticide, herbicide Soils: ~40% clay; pH 4.5 (F), 5.5-6 (S, M)
  37. 37. Q Amazon intensification trace gas patterns: How does cropland management affect CO2, N2O and CH4 in Southeastern Amazonia?
  38. 38. Do the impacts of land use propagate down the soil profile in a way that may influence trace gas emissions? 10m soil pit!
  39. 39. 15 cm 40 cm 75 cm 150 cm 250 cm 350 cm 450 cm Gas Sampling Data Thermocouple and Time-Domain Reflectometry Three pits in transitional Amazon forest (For), three in agriculture (Ag).
  40. 40. Agricultural soils are wetter, with a pronounced dip at crop rooting depth; high forest moisture variability Land use effect, p < 0.0001; depth effect, p < 0.0001; interaction, p < 0.001
  41. 41. Agricultural soils are also hotter, and less variable than forest temperatures – promoting trace gas production Land use effect, p < 0.0001; depth effect, p < 0.0001; interaction NS
  42. 42. How do these abiotic factors interact with N fertilizer management to influence trace gas emissions in cropland and forest?
  43. 43. Field measurement of N pools and GHG fluxes + 30 kgN/yr as nitrate + 45 kgN/yr as urea
  44. 44. Forest (F) Soybean (S) Soybean/Maize (M) Dry season N2O emissions are uniformly near zero (~0- 0.5 ngN/cm2/h). Surprisingly, wet season emissions remain low as well, between 1-4 ngN/cm2/h. Land uses did not significantly differ. S MF
  45. 45. While post-fertilization N2O peaks can be substantial, in several cases they barely deviated from the baseline.
  46. 46. S MF NO3 - concentrations are significantly higher in N-fertilized maize fields than in forests (p < 0.01). However, there is not a significant correlation between N2O emissions and soil inorganic N availability.
  47. 47. Forest (F) Soybean (S) Soybean/Maize (M) CO2 fluxes are highest in soybean/maize sites (p < 0.01). Comparison of row-interrow chambers indicated that cropland row chambers had fluxes ~90% higher than inter-row chambers. S MF
  48. 48. Forest (F) Soybean (S) Soybean/Maize (M) CH4 emissions in forests had strong heterogeneity within site. Forest soil uptake of CH4 was significantly larger than in agricultural soils (p < 0.001). S MF
  49. 49. What are the implications of these differences for global climate?
  50. 50. We extrapolated to an annual flux on each land use by calculating the average dry season flux, wet season flux, and “post-fertilization” flux (<15 days after N fertilization) Take-away: N2O sees re-ranking between forest/ag annual emissions with management
  51. 51. Amazonian intensification may have limited greenhouse gas consequences, with profound implications for tropical agriculture
  52. 52. Tropical forests and global change Agriculture, energy and biogeochemistry in Amazonia Drought, oxygen and biogeochemistry in Puerto Rico
  53. 53. Luquillo Experimental Forest: Historic drought
  54. 54. Q How does severe drought impact belowground biogeochemistry and GHG emissions?
  55. 55. Field array (O2 and TDR sensors, automated GHG chambers) allowed high temporal resolution data before, during and after
  56. 56. Soil moisture and O2 exhibited a threshold response to drought with lengthy persistence; valley less sensitive to O2 changes
  57. 57. Soil moisture and O2 exhibited a threshold response to drought with lengthy persistence; valley less sensitive to O2 changes
  58. 58. Greenhouse gas emissions show patterns across topographic space: particularly CO2 on slopes.
  59. 59. Iron(II) concentrations decreased post- drought, particularly in the valleys, while Iron(III) concentrations increased, associated with Iron(II) oxidation to Iron(III) after soil oxygen availability rose.
  60. 60. Inorganic phosphorus concentrations declined dramatically during the drought, possibly due to Fe-P bonding. Organic P increased slightly, possibility due to decreased decomposition rates.
  61. 61. Drought may impact tropical forest carbon storage both directly via moisture changes, and indirectly via nutrient availability
  62. 62. Summary: Land use change
  63. 63. Deforesting tropical land likely has much larger biogeochemical ramifications than intensification on tropical agricultural lands
  64. 64. Summary: Climate change
  65. 65. Climate change impacts on tropical forest functioning will likely feature complex feedbacks between nutrient cycles
  66. 66. Improving our knowledge about how global change impacts tropical forests will be critical to managing these key ecosystems in a changing world
  67. 67. Thanks very much Photo credits Flickr CC Users CIFOR Billtacular Jacsonquerubin flinner! Carine06 LeoFFreitas terrydu ggallice Icelight MODIS images via NASA Obrigada to The Silver Lab and ESPM for postdoctoral support My wonderful mentors at Minnesota: Sarah Hobbie, Steve Polasky, Jennifer Powers, Rod Venterea, and Jon Foley Colleagues at collaborating institutions: Mike Coe, Eric Davidson, Chris Neill, Marcia Macedo, Paul Lefebvre, Chelsea Nagy, Carlos Cerri, and Paulo Brando The field team at Tanguro: Santarem, Bati, Darlisson, Ebis, Sandro and Dona Lucia Supporting agencies below: Christine S. O’Connell, coconn@berkeley.edu, UC-B ESPM
  68. 68. IPCC AR5 (2014) Remaining forests will likely experience changes to precipitation timing and amount
  69. 69. Carbon storage priority changes Habitat quality priority changes Regional climate priority changes Tg C Effects Habitat Effects Reg. Clim. Effects
  70. 70. Carbon storage priority changes Habitat quality priority changes Regional climate priority changes Tg C Effects Habitat Effects Reg. Clim. Effects
  71. 71. Carbon storage priority changes Habitat quality priority changes Regional climate priority changes Tg C Effects Habitat Effects Reg. Clim. Effects

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