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Project Progress

Earth Science’s paleobiology identifies modern analogs that serve as functional scenarios for past environments inferred from proxy records. This serves Astrobiology to increase its depth and scope as the science of life in the universe. Usually, astrobiologists analyze evolutionary scenarios on systems that are progressive, of growing complexity. In contrast, we analyze regressive scenarios where evolution runs backward, in a process of decreasing complexity. To explore regressive scenarios we created model (1) combining well established practices from literature with spectroscopic, geologic and astronomic data to predict the past (“paleo”) ecosystem’s Net Primary Production (NPP).

Paleo-NPP ={tΣT (σ*Paleo-NDVI)*ε} V.O.S. (1)

(tΣT measures soil water content, σ*Paleo-NDVI measures the green biomass, ε is an energy conversion efficiency coefficient related to location and type of metabolism, and V.O.S adjusts the results to the state of the Holocene climate forcings at any given time). We use NASA-CASA model data for calibration and control. Regarding proxy records we found that (1) pollen stratigraphy offers rich, diverse information to hindcast ecosystems at coarse time scale, (2) tree rings provide the best time resolution, and (3) Neural Networks are powerful tools to extract climate-related signals from tree rings. Using South America as our ecosphere analog, we try to hindcast NPP over the last 750 years and are currently working to enlarge our databases to enable hindcasting of the last 2,500 years, the extent of the Subatlantic phase of the Holocene. Our contribution to M.L. Absy’s work in Northeastern Brazil

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shows changes in the modern ecosystem that can be captured by model (1). We collaborated to study the effects of increased ultraviolet B radiation (UV-B) on skin fibroblasts by measuring exposure to the mixture of UV-A and UV-B needed to trigger the process of apoptosis. These data are useful for planning the human exploration beyond planet Earth.