For Benefit of our Computer Science Colleagues

Ecology is a scientific discipline to study interactions of live organisms with their environmentMajor sub-disciplines:

Physiological EcologyPopulation EcologyCommunity EcologyEcosystem Ecology

Major ecological issuesBiodiversity Ecosystem services

Climate Change 101Homo sapiensHomo erectus

IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

“Climate Change” not “Global Warming”

Climate ChangesTemperature Sea Level Rise

Precipitation

• Erosion and inundationof coastal lands

• Costs of protectingvulnerable lands

Coastal Areas

• Geographic range• Health, composition, and

productivity

Forest Impacts

• Crop yields• Irrigation demand• Pest management

Agriculture

• Weather-related deaths• Infectious diseases• Air quality - respiratory

illnesses

Health Impacts

• Loss of habitat and diversity

• Species range shifts• Ecosystem services

Ecosystems

• Changes in precipitation, water quality, andwater supply

Water Resources

The Role of Bioenergy

The successful deployment of bioenergy in a climate-constrained world depends as much on continued productivity advances for food crops as on advancements for energy crops.

550 ppm Stabilization: No Improvement in Agricultural Productivity

550 ppm Stabilization: 0.5% per Year Improvement in Agricultural Productivity

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 2005 2020 2035 2050 2065 2080 2095

Unmanaged Ecosystems

Managed Forests

Crop Land

PastureLand

BioEnergy

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 2005 2020 2035 2050 2065 2080 2095

Unmanaged Ecosystems

Crop LandPasture

Land

Managed Forests

Research Need

To develop robust methods to forecast future states of ecosystems and then to assess resilience and, potentially, collapse of ecosystem services in response to changes in land use, biological invasions and climate

Projection of climate change in 4AR of IPCC

IPCC Third Report Assessmenmt

A worldwide network with over 100 manipulative experimental sites to study impacts of global change factors on ecosystem processes.

TERACC

a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide, water vapor, and energy between terrestrial ecosystem and atmosphere. At present, over 400 tower sites are operating on a long-term and continuous basis. Researchers also collect data on site vegetation, soil, hydrologic, and meteorological characteristics at the tower sites.

FLUXNET

Long Term Ecological Research (LTER) Network

LTER Network established in 1980, has 26 sites, and involves more than 1800 scientists and students investigating ecological processes over long temporal and broad spatial scales.

Synthesis across sites is one of the major challenges for LTER

NEONNEON

A DataA Data--Rich EraRich Era

The ultimate value of the diverse and abundant data will depend on their integration into models to advance our process-level understanding and ecological forecasting.

Process thinking

Data-model fusion

Synthesis and

predictionInformation contained in

data

Inverse analysis/modelingMultiple constraintsInference analysisData-model assimilation

Uses of Multiple data sets to improve models

Tree biomass growthSoil respiration

Litter fall

Soil carbon

Foliage biomass

GPP

Leaf (X1) Wood (X3)

Metabolic litter (X4)

Microbes (X6)

Structure litter(X5)

Slow SOM (X7)

Passive SOM (X8)

CO2

CO2

CO2

CO2

CO2

CO2

CO2

CO2

BuAXdtdX

+= τ

MCMC– Metropolis-Hastings algorithm

Mathematical and statistical procedure

1. Matrix to describe C flow

2. Mapping functions

Qj(A)(t) = qj(A)(t) • X(A)(t)

3. Cost function

4. Search method

⎥⎦

⎤⎢⎣

⎡−= ∑∑

==

jn

ij

ji

jm

jj tQtAQAJ

1

20

1))())((()( ν

Root (X2)

Carbon poolsCarbon pools daily analysis (lines) from 1996daily analysis (lines) from 1996--2004 and 2004 and carbon carbon poolspools daily forecast from 2004daily forecast from 2004--2012 using 100 ensembles.2012 using 100 ensembles.

27.6%

39.3%

10.5%

10.8%

6%

Analysis Forecast

Gao et al. GCB in review

parametersPartitioning

coefficientsTransfer

coefficients

NPPBiomass

LitterSOCNDVI

RadiationLand coverSoil texture

PrecipitationSoil moisturetemperature

TECOTECO

Global change

scenariosRegional carbon sinks and its variability

Regional applications

Zhou and Luo 2008 GBC

Spatial pattern of the optimal Q10 values. In general, tundra, C3 and C4 grasslands, shrublands, and croplands have higher Q10 values than deserts, bare grounds, broadleaf deciduous forests, and woodlands.

NSF workshop on data assimilationOctober 2007

TheoryReal-time data strings

ecological models

Data-model fusion

Eco-informatics

Ecological forecasting

Observation networks

Decision making

Resource management

Preparation for catastrophe

Near-term goals: To develop capability forReal- or near-time forecasts of net ecosystem exchange (NEE) at flux towersNear-time forecasts of global and regional biogoechemical processes to improve NCAR’s CLM for IPCC assessment

Ultimate goals:Automation of workflow from sensors databases

portal data assimilation ecological forecasting output analysis and visualizationData mining and spatial analysis to discover patterns

Research of the Research of the EPSCoREPSCoR ProjectProject(Data assimilation and ecological forecasting)(Data assimilation and ecological forecasting)

Sensors at eddy-flux tower

Output: NEE

Model-data fusion

forecasting

Climate forecastor

Automated1 day

5 days

10 days

1 month

3 months

6 months

12 months

Weather forecastor

Computer Server

Raw data

Processed data

VNC connections (daily)

Comprehensive package for data processing: EdiRe, TK2, Winflux et al.

Workflow Analysis and visualization

Satellite and other sources of data

Data portal Computer servers

Data assimilation algorithms

forecasting

NCAR’s CLM

Output analysis and visualization

Regional and global forecasts of biogoechemical cycles

Meta-databases Library of modules of process models

Toolbox of inversion techniques

Inverse modeling

Parameter estimation

Evaluation of model structure

Information content of data sets

Uncertainty analysis

Forecasts of future states with confidence intervals

Proposed Ecological Platform for Assimilation of Data (EcoPAD), which centers at the inverse modeling and forward predictions. EcoPAD is supported by meta databases of biogeochemical variables, libraries of modules of process models, and toolbox of inversion techniques. The inverse analysis will lead to parameter estimation, evaluation of model structure and information content of data sets, and uncertainty analysis, all of which will be fed to forward modeling for forecasting future states of ecosystems with confidence intervals.

CyberCommons

HPCServices

Data Portal and services

(Xiao)

Satellite Data

TEMDISDisease dynamics

Plant (Palmer)

Bird (Keller)Biodiversity survey Data

Implem

entation

(Neem

an)

(Neem

an)

EcoPADData Assimilation

(Lakshmivarahan, Luo)Ecological

Models

Data archival ontology retrieval QA/QC

Spatiotemporal analysis

Data mining

(Yuan)

Ecological Forecasting

Visualization (Weaver)

(Team)

(Neeman)

(Xiao)

(Luo)

Users

(Luo)

(Mc Govern & Gruenwald)

Sensor network(Gruenwald

& Luo)

19-24 25-30

Real-time forecast

31-3613-187-121-6Task