Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest

1. Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cyclein the Upper Midwest USA American Geophysical Union Fall 2005 Meeting B44B-05 Ankur R Desai, Kenneth J Davis: The Pennsylvania State University Paul R Moorcroft: Harvard University Paul V Bolstad: University of Minnesota

2. Complex Regions: 1+1≠2 • Observational data scaling and ecosystem modeling of land-atmosphere carbon dioxide flux relying solely on dominant cover types is difficult in regions with complex land cover arising from topography, land management and other biotic & abiotic interactions (e.g., light environment, soil type)

3. Disturbance and Land Cover • Past and current land use and forest harvest leaves its imprint on modern day land cover on the order of 100 yrs or longer in forested regions • This imprint has the potential to alter land-atmosphere carbon exchange magnitudes and patterns • The upper-Midwest was heavily clear-cut in the late 19th / early 20th century

4. The Upper Midwest • Today, the region is a complex, actively managed, heavily forested region with extensive wetland cover • The densely-instrumented landscape is ideal for testing the roles of disturbance, management and scaling on the regional carbon cycle

5. A Very Tall Tower • Park Falls, WI - WLEF • Regionally representative CO2 fluxes at 30-396 m • Tower shows small source (positive NEE) of CO2 to atmosphere, in contrast to stand-scale towers in region • Larger ecosystem respiration (ER), similar gross production (GPP) to stand-scale towers • Are we undersampling certain stand ages (young/old) or ecosystems (e.g., wetlands)?

6. Stand Scale Observations • 12+ stand scale eddy covariance towers in region • No significant difference in meteorology among sites • Stand age/cover lead to significant differences in flux • Coherent interannual variability in NEE and GPP

7. Multi-tower Aggregation Scaling • Stand-scale towers were scaled to regional flux, based on: • LandSat 30m land cover type • Forest Inventory Analysis stand age • Two equation parameter optimization • Sites are assumed to observe same climate – mostly true

8. Regional Flux Comparisons • Multi-tower aggregated fluxes (NEP, ER, GPP) for summer 2003 (blue) has smaller ER and larger GPP than tall tower (red) (Desai et al, in press) • However when tall tower fluxes were decomposed & downscaled using footprint models (Wang et al., submitted) and regionally aggregated by land cover density (green) – upscaling and downscaling agree better

9. Biogeochemical models • We can further investigate regional flux with models • Biome-scale biogeochemical models treat each “cell” as a single plant functional type (or fractions of a few) and 1-2 canopy layers with grid-average values of biomass/fluxes • Age can only be modeled by following a cell with time as it builds and loses biomass

10. Dynamic Ecosystem Models • On the other side of the spectrum are “gap” models that simulate the growth and fate of every plant with explicit interaction among them • Computationally expensive • Difficult to parameterize • Can be complicated to scale • Instead, we apply a height-and-age structured gap model to the region that uses concepts of statistical mechanics and ensemble averaging to simulate the dynamics of the mean-moment ensemble of gaps • Moorcroft et al, 2001, Ecological Monographs • Grid cell consists of multiple patches of different ages • Patches also segregated by disturbance type • Patches contains multiple cohorts of size and plant type • Patch age affects light availability

11. The Ecosystem Demography Model • Farquhar leaf-level photosynthesis with soil water/N limitations and simple canopy light extinction • Mean-moment differential equations for cohort density, active plant/root tissue size, non-active plant biomass, and patch CWD, fast, structural, slow and passive soil C and water pools • Boundary conditions controlled by reproduction, mortality, disturbance and phenology Source: Moorcroft et al., 2001 Source: Hurtt et al., 2002

12. Model Data Assimilation • Region divided by into soil/topographic sub-sites: • mesic upland (N hardwoods/hemlock), xeric upland (N pines/ash-oak), lowland (shrub and forested wetlands) • Constrained parameters • USFS FIA: mortality, reproduction, harvest • Chamber fluxes: component respiration rates, VcMax • Biometric: site allometry, specific leaf area, C:N • Input variables • Meteorology: tower and NCDC air temperature, soil temperature, PAR, CO2, humidity, precipitation • Land use/cover: Public land survey for presettlement vegetation (Schulte, 2002), Hurtt et al. land use change • Time steps • Hourly biogeochemistry, adaptive (days-month) growth and allocation, monthly ecosystem dynamics

13. Model Setup • Model sub-sites (mesic, xeric, wet, water/ag/barren) summed by % landcover in 65-km radius around tall-tower • Water, agricultural and barren lands are assumed to have 0 NEE, ER, GEP • Four model scenarios: • Full run (red) • No anthropogenic disturbance (blue) • Pre-industrial CO2 with anthropogenic disturb. (light red) • No CO2 increase or anthropogenic disturbance (cyan) • Each scenario and sub-site run from 1800-2004 • Forest tent caterpillar infestation in 2001 included • Results compared to tall tower (LEF/black), footprint decomposed and aggregated (LEF*) and stand-scaled tower based upscaled fluxes • Caveat: results are very preliminary at this point

14. Results: Land Cover in 2004

15. Results: Mean Fluxes 1997-2004

16. Results: Comparison to Tall Tower

17. Results: Comparison to Tower Scaling Jun-Aug 2003 LEF = tall tower flux LEF* = downscaled regionally-integrated flux Towers = multi-tower upscaling Model = ED Full Run

18. Results: Impact of Stand Age

19. Implications • Model results fall within range observed by tall tower and by footprint-based downscaling and stand scale upscaling • More observation sites needed in wetlands and young forests – currently underway • Carbon fertilization significantly enhances net uptake today in response to logging 100 yrs ago • May be artifact from lack of CO2 downregulation • Modeled ecosystem respiration is lower than observed at tall tower, but larger than stand scale aggregated towers • Young sites (esp. wetlands) have large ER:GPP ratio, leading to positive NEE – role of disturbance residue • Carbon sink strength declines in mature and old sites except for xeric sites which continue to strengthen • Mesic sites: age of max. ER precedes age of max. GPP • Sampling of dominant cover types (mature mixed forest) cannot solely explain regional carbon flux

20. Future Work • Uncertainty analysis of model output • Continued investigation of • Climate-carbon flux coupling as a function of stand type • Observation network density needed for scaling • Minimum resolution required for spatial data • Scaling to larger and smaller regions • Role of local vs. global parameterizations • Carbon fertilization effects • Forest product lifecycle, net biome productivity • Incorporation of wetland dynamics and biogeochemistry • Comparison to atmospheric tracer based regional carbon flux observations: see next two talks – B44B-06 (Davis) / B44B-07 (Uliasz) • Incorporation of new biometric and flux data: see talk after that – B44B-08 (Bolstad) • Running model into the future with IPCC scenarios