The Dance of Pattern & Process along the Road to Prediction Change & its Prediction in Biology or NASA Biodiversity Research to Ecological Forecasting. Woody Turner Biodiversity & Ecological Forecasting Team Meeting Westin Grand Hotel Washington, DC August 29, 2005.
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The Dance of Pattern & Process along the Road to PredictionChange & its Prediction in BiologyorNASA Biodiversity Research to Ecological Forecasting
Biodiversity & Ecological Forecasting
Westin Grand Hotel
August 29, 2005
(Mary Helen Lowry, 1978)
On the origin of species over 2300 years ago
“Another matter which must not be passed over without consideration is, whether the proper subject of our exposition is that with which the ancient writers concerned themselves, namely, what is the process of formation of each animal; or whether it is not rather, what are the characters of a given creature when formed. … For the process of evolution is for the sake of the thing finally evolved, and not this for the sake of the process. Empedocles, then, was in error when he said that many of the characters presented by animals were merely the results of incidental occurrences during their development;….” (Aristotle, De Partibus Animalium Book I, Chapter 1)
The concept of pattern or regularity is central to science. Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself. Robert MacArthur in Geographical Ecology 1972
A Fundamental Challenge for Biology Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself.
Forecasting’s Legacy, e.g.: Weather Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself.
A Plethora of Biodiversity Data Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself.
Forest Inventory and Analysis National Program
IUCN Red List
World Database on Protected Areas
The Species Analyst
Global Mammal Assessment
ESMF: A Tool for Model Coupling Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself.
(slide from NASA/Don Anderson)
Two of Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself. Science’s Top 25 Questions
Systems approach. Circuit diagrams help clarify nerve cell functions.
Science, Vol 309, 1 July 2005
> What Determines Species Diversity?
CREDIT: MICHAEL T. SHIPLEY
> How Will Big Pictures Emerge From a Sea of Biological Data?
“New institutions around the world are gathering interdisciplinary teams of biologists, mathematicians, and computer specialists to help promote systems biology approaches” – Sounds a little like ESMF
Outside In: Niche Definition + Statistics Pattern implies some sort of repetition…. The existence of repetition means some prediction is possible—having witnessed an event once, we can partially predict its future course when it repeats itself.
(with thanks to Robert MacArthur)
Stability (e.g., Climate)
Holdridge Life Zones
The Physical Drivers of Life Vegetation:
Nemani et al. 2003. Science 300:1560–1563.
Energy Budget = f ( Feeding, Resting, Migratory Flight)
Challenge: Can we link “Outside In” & “Inside Out” Approaches?
(Farmer and Wiens, 1998)
Rn - H - lE + M = 0
(figures courtesy of GSFC/Jim Smith)
Trophic Models To Understand Relationships
Little Rock Lake in Wisconsin; produced by Neo D. Martinez of San Francisco State University,
Romberg Tiburon Center for Environmental Studies
Waide et al. surveyed 200 relationships between species richness and productivity in different systems (aquatic and terrestrial) and found 30% unimodal, 26% positive linear, 12% negative linear, and 32% not significant. (R.B. Waide et al. in Annu. Rev. Ecol. Syst. 1999, 30:257-300)
Issue of scale? At smaller scales see more niche partitioning & competition effects while at larger scales see more environmental effects (“the good life”)?—Melinda Smith at ESA Annual Mtg. 2005 Or is it a matter of Experimental systems vs. Natural systems?—Tom Stohlgren at ESA Annual Mtg. 2005
Native Species Richness
Native Species Richness
Big Question: Climate Variability & Abundance Vegetation:
(Source: UME/Fei Chai)
Food Webs Are Dynamic. The Players Change But The Plot Remains.
The food web of Tuesday Lake, 1984. The width of the horizontal bars shows the body mass (log10 kg), number (log10 individuals per m3), and biomass (log10 kg/m3), respectively, of each species. The vertical positions of the species show trophic height (20). Despite a major change in species composition, following a manipulation, this energetic setup of the food web remained roughly the same (19). T. Jonsson, J. E. Cohen, S. R. Carpenter, Adv. Ecol. Res. 36, 1 (2005) cited in Science by de Ruiter et al. (2005) 309:68-71.
Big Question: Molecular Data & Hindcasting Life Vegetation:
Feedbacks to climate & us start here.
Helicobacterium pylorii Genome from:
(from USGS Global Visualization Viewer)
A Grand Synthesis for the 21st Century
As usual, the oceanographers are ahead! Vegetation:
Grand Challenge: Understanding this Variety Vegetation:
In understanding lies the road to prediction
(e.g.: if we want to understand the biogeochemical cycling of carbon &/or other elemental cycling, we need to know other half of ecosystem equation)
Integrated global analyses Vegetation:
Carbon Cycle and Ecosystems Roadmap
Human-Ecosystems-Climate Interactions (Model-Data Fusion, Assimilation); Global Air-Sea Flux
High-Resolution Atmospheric CO2
Southern Ocean Carbon Program, Air-Sea CO2 Flux
Process controls; errors in sink reduced
Models w/improved ecosystem functions
T= Technology development
Physiology & Functional Types
Reduced flux uncertainties; coastal carbon dynamics
= Field Campaign
Global Ocean Carbon / Particle Abundance
Reduced flux uncertainties; global carbon dynamics
Goals: Global productivity and land cover change at fine resolution; biomass and carbon fluxes quantified; useful ecological forecasts and improved climate change projections
Vegetation 3-D Structure, Biomass, & Disturbance
Terrestrial carbon stocks & species habitat characterized
Global CH4;Wetlands, Flooding & Permafrost
CH4 sources characterized and quantified
Global Atmospheric CO2 (OCO)
Regional carbon sources/sinks quantified for planet
N. American Carbon Program
N. America’s carbon budget quantified
Land Use Change in Amazonia
Effects of tropical deforestation quantified; uncertainties
in tropical carbon source reduced
2002: Global productivity and land cover resolution coarse; Large uncertainties in biomass, fluxes, disturbance, and coastal events
Models & Computing Capacity
Land Cover (Landsat)
Land Cover (OLI)
Ocean Color (SeaWiFS, MODIS)
Vegetation, Fire (AVHRR, MODIS)
Vegetation (AVHRR, MODIS)
Global C Cycle
Global C Cycle
Ecological Forecasting Roadmap Vegetation:
“If-Then” Scenarios for Ecosystem Responses to Change/Disturbance
Integration of remotely-sensed data with various model types, e.g.: ecosystem, ecological niche, population & habitat viability, biogeography, biogeochemistry, & regional ocean & atmospheric models -- as well as the development of new predictive models
Species Distribution Forecasting System > biodiversity/stability/ productivity links
Ongoing global land cover change product; global precipitation data
Soil surface moisture, sea surface salinity, global river discharge measurements
Species distribution models with improved accuracy
Operational SERVIR, Protected Areas Management System, & Marine Fisheries Forecasting System DSS’s
Vegetation structure & disturbance from active sensors; new data on physiology & functional groups (hyperspectral/fluorescence)
Prototype Marine Fisheries Forecasting System DSS for fisheries management; also Protected Areas Management System DSS incorporating species habitat & demographic data into a planning tool
Regional ocean models coupled to ecosystem models; global land cover change product
Initial operation of Regional Monitoring & Visualization System DSS (SERVIR) for environmental management & sustainable development in Central America
Prototype predictive models linking remotely-sensed environmental parameters to changes in terrestrial & aquatic ecosystems
Operational ecological forecasting systems supporting environmental & natural resource management for sustainable development
Assessment of land cover change/climate impacts on ecosystems
EOS & global land cover observations; early coupling of regional climate & ecosystem models
Steady improvement in models linking functional, structural, spatial, & temporal environmental measurements (ongoing measurements include: land cover, ocean color, primary productivity)
Ecological Forecasting: Vegetation: Observations & Models for Global Management
EARTH SYSTEM MODELS
DECISION SUPPORT TOOLS
SERVIR (Spanish acronym for Regional Visualization & Monitoring System)
VALUE & BENEFITS
Protected Area Management (with VISTA & TOPS)
January 25, 2005