# Presentation: 459737

## The Dance of Pattern & Process along the Road to PredictionChange & its Prediction in BiologyorNASA Biodiversity Research to Ecological Forecasting

**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**

**Notes:**
Biological science like many sciences (e.g., geology & climatology) seems to be becoming more dynamic these days (catastrophe, threshold or nonlinear responses, chaos theory).  It is this dynamism in biology/ecology we seek to understand through the interplay of pattern and process, which define change in biology/ecology.  It is this change we seek to predict.  Why?  Because whether we intend to or not we are managing our planet’s ecosystems for good or ill at all scales.  It is time to start acting like it.  Our goal is to understand the dance of pattern and process.  Biodiversity represents both the result of and the context for this dance.   

## “Nothing has changed since the Greeks.”

**“****Nothing has changed since the Greeks.”**
**	****	****	****	****(Mary Helen Lowry, 1978)**

**“****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) **

**Aristotle**
**384-322 BC**

**Empedocles**
**c.495-c.435 BC**

**On the origin of species over 2300 years ago**** **

**Notes:**
For 2000 years, Aristotle’s view of the primacy of form (pattern) held sway.

## 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

- 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

**Notes:**
MacArthur the intellectual father of much of what we try to do in using RS tools to understand and answer questions relevant to biodiversity.

## A Fundamental Challenge for Biology

**A Fundamental Challenge for Biology**

**(http://ccinfo.ims.ac.jp/periodic/periodic.jpg)**

**Notes:**
Not only a challenge for biodiversity but for all biology and all ecosystem management.

## Forecasting’s Legacy, e.g.: Weather

- 340 BC: Aristotle’s *Meteorologica*
- 1590s: Galileo’s thermometer
- 1643: Torricelli’s barometer
- 1860s: Telegraphs link weather stations
- 1904-1922: Numerical weather forecasts
- 1920s: Invention of the radiosonde
- 1960s: First meteorological satellites & improved hurricane warnings
- 1980s-1990s: Coupling of atmosphere/ocean/land surface models (SiB, BATSbiophysics) & early climate forecasts (ENSO predictions)
- Mid to Late 1990s: Dynamic Global Vegetation Models for GCMs (e.g.: LPJ, Triffid, IBIS)

**Notes:**
Dance of Patter & Process:  Pattern=observations & experiments & Process=theory & methods

## Slide 6

## A Plethora of Biodiversity Data

**Global Mammal Assessment **

**Forest Inventory and Analysis National Program**

**A Plethora of Biodiversity Data**

**GenBank **

**The Species Analyst**

**IUCN Red List**

**World Database on Protected Areas**** **

## Models allow:

**Models allow:**
**Assimilation of data from a number of sources/platforms**
**Translation of our understanding of physical & ecological processes into numerical form**
**Tests of our understanding of these processes in the form of predictions**** **

## ESMF: A Tool for Model Coupling

**(slide from NASA/Don Anderson)**

**ESMF: A Tool for Model Coupling**

**Notes:**
ESMF is a tool for allowing different GCMs with different grids and time steps to talk to one another by regridding inputs from one to match another, e.g., allowing an NCAR atmosphere model, a GFDL ocean model, and NSIPP land model using discrete grids and time stepping to regrid to a common framework.  The “cost” is to the those who have to ensure that the appropriate “metadata” are coded with the model. 

## Two of Science’s Top 25 Questions

**> What Determines Species Diversity?**** **

**> How Will Big Pictures Emerge From a Sea of Biological Data?**** **

***Science*****, Vol 309, 1 July 2005**

**Two of *****Science’s***** Top 25 Questions**

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- CREDIT: MICHAEL T. SHIPLEY** **

**Systems approach. Circuit diagrams help clarify nerve cell functions.**** **

**“****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**

## Some Other Big Questions

- How does climate variability affect the abundance of organisms?
- How does climate change affect the distribution of organisms?
- Are the organisms in communities fungible, e.g.: how stable are trophic webs at retaining their function?
- How does biodiversity relate to the functioning of ecosystems & what are the effects of spatial scale?
- From all of the above, what are the hottest of the hot spots for retaining maximum species diversity?
- What are the best RS proxies for ecosystem diversity and ecosystem health (e.g., NDVI, NPP, soil moisture, SST/SSH & location of fronts, vegetation structural complexity, rates of disturbance, rates of upwelling, etc.)?  And what scales are necessary?
- Can we catch evolution in action by first correlating environmental changes at landscape/broader scales with genomic/proteomic changes?

## Outside In: Niche Definition + Statistics

**Patterns of**
**Species Diversity**

**Productivity**

**Environmental **
**Stability (e.g., Climate)**

**Habitat Structure**

**Outside In: Niche Definition + Statistics**

**(with thanks to Robert MacArthur)**

## Using Climate (Temperature & Moisture) to Predict Vegetation: 

- (http://www.icsu-scope.org/downloadpubs/scope56/image/Fig16.1.gif)

**Using Climate (Temperature & Moisture) to Predict Vegetation: **
**Holdridge Life Zones**

**Notes:**
1967 effort 
MacArthur noted it had the merit of using both T and moisture and could give a “good general idea” of how changes in climate might affect vegetation. 

## The Physical Drivers of Life

**Nemani et al.  2003.  *****Science***** 300:1560–1563.**

**The Physical Drivers of Life**

## Inside Out: Physiology/Energetics to Niche

*Rn - H - lE +  M = 0*

***(Farmer and Wiens, 1998)***

***Energy Budget = f ( Feeding, Resting, Migratory Flight)***

**(figures courtesy of GSFC/Jim Smith)**

**Challenge: Can we link “Outside In” & “Inside Out” Approaches? **

## Biological Drivers (e.g., competition & predation):

- http://www.chadevans.co.uk/asite/Alevel/u03/ln/energyflow2_files/image005.gif

- Little Rock Lake in Wisconsin; produced by _[Neo D. Martinez](http://online.sfsu.edu/~webhead/)__ of San Francisco State University, _
- _[Romberg Tiburon Center for Environmental Studies](http://rtc.sfsu.edu/)_

**Biological Drivers (e.g., competition & predation):**
**Trophic Models To Understand Relationships**
**Among Organisms**

**Notes:**
The flow of energy through trophic webs is how to unite outside  in and inside out approaches.

## Big Questions: Biodiversity & Ecosystem Function (& Scale)

- Species
- Richness

- NPP

- Species
- Richness

- NPP

- Native Species Richness

- Non-
- Native
- Species
- Richness

- Native Species Richness

- Non-
- Native
- Species
- Richness

**Big Questions: Biodiversity & Ecosystem Function (& Scale)**

- 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

- (backdrop: http://cedarcreek.umn.edu/research/biodiversity.html)

## Big Question: Climate Variability & Abundance

**(Source: UME/Fei Chai)**

**Big Question: Climate Variability & Abundance**

## Big Question: Disturbance & Trophic Web Stability

**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: Disturbance & Trophic Web Stability**

**Food Webs Are Dynamic. The Players Change But The Plot Remains.**

**Notes:**
Tuesday Lake, Michigan: removed 3 planktivorous fish species & added one piscivorous fish species, led to big changes in community structure but almost no impact on species richness, which went from 56 in 1984 to 57 in 1986 with about 50% of the species being replaced by new incoming species in less than 2 years; energetic setup of the food web, in terms of body size distributions & abundances over trophic levels, remained roughly the same 

## Big Question: Molecular Data & Hindcasting Life

**Big Question: Molecular Data & Hindcasting Life**

## Where To?

*Helicobacterium pylorii* Genome from:
- http://biocrs.biomed.brown.edu/Books/Chapters/Ch%2038/Pylori-Genome.gif

- (from USGS Global Visualization Viewer)

**A Grand Synthesis for the 21****st**** Century**

**Feedbacks to climate & us start here.**

## As usual, the oceanographers are ahead!

**As usual, the oceanographers are ahead!**

## Grand Challenge: Understanding this Variety

**BIOGEOCHEMISTRY**

**BIODIVERSITY**
**“****Terra Incognita”**

- 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)

**Grand Challenge: Understanding this Variety**

## Slide 24

**Notes:**
Presence of Protaphorura armata reduced by 32% the C respired from the mycorrhizosphere.

**Carbon Cycle and Ecosystems Roadmap**

**T**

**2002**

**2010**

**2012**

**2014**

**2015**

**2004**

- Reduced flux uncertainties;   global carbon dynamics

- Funded

- Unfunded

- Global Ocean Carbon /     Particle Abundance

- N. America’s carbon budget quantified

-      Global Atmospheric CO2 (OCO)

**2006**

**2008**

** **Reduced flux uncertainties; coastal  carbon dynamics

**NA Carbon**

**NA Carbon**

**Global C Cycle **

**T** = Technology development

- Regional carbon sources/sinks quantified for planet

**IPCC**

**IPCC**

- Effects of tropical deforestation quantified; uncertainties
- in tropical carbon source reduced

- = Field Campaign

-       Physiology & Functional Types

**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

**     ****T**

- Terrestrial carbon stocks & species habitat characterized

- Models w/improved ecosystem functions

- High-Resolution Atmospheric CO2

** **Sub-regional sources/sinks

- Integrated global analyses

- CH4 sources characterized and quantified

**P**

- Vegetation (AVHRR, MODIS)

- Ocean Color (SeaWiFS, MODIS)

- Land Cover (Landsat)

-      LDCM

- Land Cover (OLI)

- Vegetation, Fire  (AVHRR, MODIS)

-    Ocean/Land (VIIRS/NPP)

-    Ocean/Land (VIIRS/NPOESS)

- Models & Computing Capacity

- Case Studies

- Process Understanding

- Improvements:

- Human-Ecosystems-Climate Interactions (Model-Data Fusion, Assimilation); Global Air-Sea Flux

**T**

- Partnership

- N.  American Carbon Program

**           **Land Use Change in Amazonia

- Global CH4;** **Wetlands, Flooding & Permafrost

**Global C Cycle **

**                ****Knowledge Base**

**2002:  Global productivity and land cover resolution coarse; Large uncertainties in biomass, fluxes, disturbance, and  coastal events**

- Systematic Observations

-  Process controls; errors in sink reduced

- Coastal Carbon

- Southern Ocean Carbon Program,            Air-Sea CO2 Flux

## Ecological Forecasting Roadmap

**Species Distribution Forecasting System >  biodiversity/stability/ productivity links**

**Species distribution models with improved accuracy**

**Prototype Marine Fisheries Forecasting System DSS for fisheries management; also Protected Areas Management System DSS incorporating species habitat & demographic data into a planning tool**

**Aqua**

**NPP/VIIRS**

**NPOESS**

**Landsat 7**

**Terra**

**EOS & global land cover observations; early coupling of regional climate & ecosystem models **

**Assessment of land cover change/climate impacts on ecosystems**

**Prototype predictive models linking remotely-sensed environmental parameters to changes in terrestrial & aquatic ecosystems**

**Initial operation of Regional Monitoring & Visualization System DSS (SERVIR) for environmental management & sustainable development in Central America   **

**Operational SERVIR, Protected Areas Management System, & Marine Fisheries Forecasting System DSS’s **

**Soil surface moisture, sea surface salinity, global river discharge measurements**

**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**

**“****If-Then” Scenarios for Ecosystem Responses to Change/Disturbance**

**2003**

**2013**

**2005**

**2009**

**2011**

- Steady improvement in models linking functional, structural, spatial, & temporal environmental measurements (ongoing measurements include: land cover, ocean color, primary productivity)

**Vegetation structure & disturbance from active sensors; new data on physiology & functional groups (hyperspectral/fluorescence)**

**Current trajectory**

**Operational ecological forecasting systems supporting environmental & natural resource management for sustainable development**

**2007**

**Ecological Forecasting Roadmap**

**GPM**

**HYDROS**

**Aquarius**

**Regional ocean models coupled to ecosystem models; global land cover change product**

**TRMM**

**SRTM**

**Ongoing global land cover change product; global precipitation data **

## Ecological Forecasting:Observations & Models for Global Management

***Data***

**DECISION SUPPORT TOOLS**

**VALUE & BENEFITS**

**EARTH SYSTEM MODELS**

- Predictions

****Future Mission***

- 60

**SERVIR ****(Spanish acronym for Regional Visualization & Monitoring System)**

**Monitor changes in land cover, weather, & fires to assist the sustainable management of the Mesoamerican Biological Corridor  **

**Impact of ENSO & PDO Events on Fisheries**

**Combine physical ocean models & ecosystem trophic-level models to predict impacts of climatological changes on regional fisheries**

**Protected Area Management (with VISTA & TOPS)**

**Coordinate multi-NGO effort to pool resources for monitoring protected areas per CBD 2010 goal**
**Link to President’s illegal logging initiative & CBFP**

- Observations

**Ecological Forecasting:****Observations & Models for Global Management**

- Predictions

**Management of a global hotspot of biodiversity, i.e. Mesoamerica, at a regional scale through the coordination of the activities of 7 countries - a model for other regions.**
**Predict the impacts of changing land use patterns & climate on the ecosystem services that support all human enterprises.**
**Develop ecological forecasts with reliable assessments of error.**

**Ecological Niche** (GARP)
**Scalable spatio-temporal models a la NREL**
**Regional Ocean Models & Empirical Atmospheric Models coupled with ecosystem trophic models**
**Ecosystem **(ED, CASA)
**Population & Habitat Viability Assessment **(VORTEX, RAMAS GIS)
**Biogeography **(MAPSS, BIOME3, DOLY)
**Biogeochemistry **(BIOME-BGC, CENTURY, TEM)

_**Land cover**_**:** MODIS, AVHRR, Landsat, ASTER, ALI, Hyperion, IKONOS/QuickBird
_**Topography/Vegetation Structure**_**:** SRTM, ASTER, IKONOS, LVIS, SLICER, Radars
_**Primary Productivity/Phenology**_**:** AVHRR, SeaWiFS, MODIS, Landsat, ASTER, ALI, Hyperion, IKONOS, QuickBird, AVIRIS
_**Atmosphere/Climate**_**:***  *AIRS/AMSU/HSB, TRMM (PR, LIS, TMI), AVHRR, MODIS, MISR, CERES, QuikScat
_**Ocean**_**:** AVHRR, SeaWiFS, MODIS, TOPEX/Poseidon, JASON, **AQUARIUS**
_**Soils**_**:** AMSR-E, AIRSAR

**Species Distributions**
**Ecosystem Fluxes **
**Ecosystem Productivity **
**Population Ecology **
**Land Cover Change**

**Land Cover/Land Use & Disturbances (e.g., fire) **
**Species Composition**
**Biomass/Productivity**
**Phenology**
**Vegetation Structure**
**Elevation**
**Surface Temperature**
**SST, SSH, Circulation, & Salinity**
**Atmospheric Temp.**
**Soil Moisture**
**Precipitation**
**Winds**

**EARTH OBSERVATORIES**

**January 25, 2005**

*(example models)*

**Notes:**
Ecological forecasting uses Earth observation data and models to predict the impacts of environmental change on the ecosystems that support the existence of life on Earth.  It also links the physical world of climate and geology to the living world of biology and ecology.  The goal is reliable forecasts that allow decision makers access to science-based tools in order to project changes in living systems.  These forecasts should incorporate knowledge of uncertainties and estimates of error and allow those making decisions to compare the outcomes of alternative policies.

## Goals for Meeting

**Bring people together**
**Suggest additional questions**
**Define technological needs**
**Make programmatic connections**
**Among research activities**
**Between research & educational activities**
**Between projects & Center activities**
**Among agencies**