Early Warning System: monitoring aspect
Celso von Randow
Earth System Science Center - INPE
[email protected]
EWS framework
In situ monitoring
stations
Remote sensing
monitoring system
Monitoring,
analysis and
prediction
Policy
responses
EARLY
WARNING
SYSTEM
Communicating
alerts
Modeling System
• Monitoring system
• Modeling System
• Analysis Tools
• Communications
division
Early Warning System
• Which ecosystem services and other
properties of the Amazon would be important
to monitor and prevent from tipping into a
degraded state ?
• What to warn about?
– Degradation of ecosystem services in what time
scales (years – decades) ?
– Not only critical transitions, but also gradual
change
Critical indicators
• The basis of such a system is long-term
monitoring of critical indicators
• These indicators should be quantities that are
relatively accessible, and easy to monitor at high
temporal and/or spatial resolution.
• should represent the variability of the Amazon
ecosystem services and other important tipping
phenomena
=> their behaviour near critical transitions should
reliably point to imminent change in the state of
that particular ecosystem service.
Tipping point early warning signals
System being
forced past a
bifurcation point
yt+1 = ayt + sht
a = exp(- kDt)
k→0 and a→1 at bifurcation
Alternative stable states?
Frequency of Tree Cover (Global)
Treeless state:
T < 5%
Forest state:
Savanna state:
5% ≤ T < 60%
T ≥ 60%
Hirota et al., Science, 2011
Tree cover X MAP (global):
Scheffer et al., TREE, 2003
Hirota et al., Science, 2011
Tree cover X MAP (global):
Scheffer et al., TREE, 2003
Hirota et al., Science, 2011
Statistical
procedure (Livina
et al., 2010)
confirmed
3 classes:
Analysis tools
• Generic Early Warning indicators – detection
on basis of change in variability
Analysis tools
• Generic Early Warning indicators – detection
on basis of change in variability
• Detection on basis of exceedance of critical
thresholds - analysis of trends and changing
trends
Analysis tools
• Generic Early Warning indicators – detection
on basis of change in variability
• Detection on basis of exceedance of critical
thresholds - analysis of trends and changing
trends
• Identification of outliers from analysis of
PDFs – (given a range of conditions that
sustain a particular forest, look into
predictions of extremes)
List of possible variables to monitor
• Sea Surface Temperature (SST) - indicator of
global-scale change
• Precipitation (patterns, quantity, dry season
length…) primary driver as well as an ecosystem
service that can be affected
• Climate modes (ENSO, Atlantic Oscillations, etc) often correlated indicators of high-impact
changes or episodes in Amazonia
• River flow and discharge
• Evapotranspiration - prime driver of recycling
List of possible variables to monitor
• overall vegetation productivity changes –
[CO2] over the tropical belt + anthropogenic
emissions
• Biomass - remote sensing (eg S-band Radar)
and well-referenced growth bands in forest
plots across the basin
• Water use efficiency from tree-ring & gas
exchange monitoring
• Remote sensing indices (NDVI , EVI)
List of possible variables to monitor
• Fires (remote sensing and in-situ
observations) – not simply occurrence or area,
but also fire effects (e.g. type of vegetation
affected and recovery of previously burned
areas
• Economic indicators, such as the GDP of the
region, transport, trade and migration
patterns
• Exposure and Vulnerability (?)
COSMOS (COsmic-ray Soil Moisture Observing System)
Could it be used to monitor ‘flammability’ of the forest?
Monte-Carlo Simulation of Neutron Density
This is largely a soildependent “shift”,
SO ONLY ONE FIELD
CALIBRATE NEEDED
In drier soil,
more neutrons escape
Monte-Carlo Simulation of Neutron Density
COSMOS probes detect
neutrons at two energies, but
use “fast” neutrons for soil
moisture detection because
calibration is less sensitive to
the chemistry of the soil
In moister soil,
less neutrons escape
(thermal neutrons give
information on above-ground
water, e.g. snow cover)
Fast Neutron
Detector
Thermal Neutron
Detector
COSMOS (COsmic-ray Soil Moisture Observing System)
Example COSMOS Data for the San Pedro Basin
Gravimetric samples are in red, with sampling error
Soil moisture from cosmic-ray neutron data compared with gravimetric samples
5.0
4.5
For the (single)
calibration of a
COSMOS probe
(made at installation),
soil will be sampled at
3 depths, 8 directions,
and 3 radii around the
probe
(i.e., 72 samples).
Gravimetric water content
How many point
measurements
are needed to
get a similar
(2%) precision in
area-average
soil moisture?
4.0
3.5
3.0
2.5
2.0
1.5
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Day in July 2007
Diurnal Cycles
(moisture redistribution)
Institutional and practical embedding
• From stakeholders consultation:
– EWS: MMA, MAPA, MME, MDA
– ‘Users’ / Policy makers: MMA, SAE (Secret.
Assuntos Estratégicos), CENSIPAM (Centro Gestor
e Operacional do Sistema de Proteção da
Amazônia), Órgãos Estaduais de Meio Ambiente
(OEMAs)
Communication
• Communication of complex issues to nonscience audience is a major challenge
• Design should be (as much as possible)
stakeholder-driven (e.g. focus on critical
transitions in environmental conditions or
direct impacts in ecosystem services) ?
• Reduce risk of false positives
Conclusions
Design of an Early Warning System for critical transitions in
the Amazon region:
• Requires a multi-disciplinary approach and involvement of
relevant stakeholders
• Based on long-term monitoring of critical indicators that
should be relatively accessible to monitor and should
represent the variability of relevant ecosystem services
• Their behaviour near critical transitions should reliably
point to imminent change in the state of that particular
service.
• Through model analysis and analysing data sets, the most
efficient monitoring and analysis tools need to be designed
• Communication is a major challenge for effective policy
actions
WP2 runs (Moore protocol)
A
LPJml
OK
INLAND
Ongoing
B
C
D
OK
OK
Ongoing
JULES
OK
OK
ORCHIDEE
OK
ongoing
Simulation A (Potential vegetation A): natural disturbances + no land-use change +
changing climate (recycling the SHEF driver) + changing CO2.
Simulation B (Potential vegetation B): natural disturbances by excluding fire + no landuse change + changing climate (recycling the SHEF driver) + changing CO2.
Simulation C ( Changing climate ): This simulation need to be achieved by two steps: 1)
natural disturbances + no land-use change + changing climate (recycling the SHEF driver)
+ changing CO2 from 1715 to 1970; 2) natural disturbances + no land-use change +
changing climate + constant CO2 (=325.713 ppm) from 1970 to 2008.
Simulation D (Full changes): natural disturbances + land-use change + changing climate +
changing CO2.
WP3 runs
How to achieve a sustainable future?
Environmental
Economic
Low Social Development
“In 2050, Brazil is one of the main
economies of the world, but
structural inequalities in society
persist. Land in rural areas is
highly concentrated, urban areas
remain violent, segregated, with
bad quality services in poor
neighborhoods.”
Economic
National Storylines
(based on Nobre et al., forthcoming)
“Well managed natural resources,
ecosystem services provision and
low greenhouse emissions”
High Environmental
Development
Vision A:
High, High
Sustainable
Vision B
Low, High
A
Vision D
Low, Low
Vision C
Low, High
Low Environmental
Development
“Badly managed natural resources,
few natural vegetation areas
remaining, and high greenhouse
emissions.”
Social
Environmental
Economic
High Social Development
“In 2050, Brazil is one of the main
economies of the world. Social
indicators also place Brazil among
the most equitable and socially fair
countries in the world. Society as a
whole has access to high quality
education, health services, economic
opportunities, supported by strong
institutions. ”
Social
Economic
LUCC spatially explicit models
adapted from Verburg et al., 2006
LuccME / BrAmazonia
model summary
Selection of relevant policies
Policies
International and national non-Amazonian:
• UNFCCC: Decisions taken during COP 17 change the accounting rules
applying to the land-use sector and to wood converted to products. These
new rules are, however, unlikely to increase pressure to import wood from
non-EU nations to an important extent.
• Nationally appropriate mitigation actions (NAMAs). These are voluntary
actions by development countries and countries in transition to reduce
GHG emissions, aiming at seeking and matching international financial,
technology, and capacity-building support for proposed actions and at
recognizing individual actions which may be implemented without
international support. NAMA registry is not yet operational and given the
vague definition and the wide range of support options, they can be
expected to strongly overlap or to be combined with instruments such as
credit generation for the carbon markets.
• Reducing emissions from deforestation and forest degradation (REDD) Multilateral initiatives: UN-REDD programme, Forest Carbon Partnership
Facility (FCPF), Forest Investment Program (FIP), and REDD+ partnership;
bilateral agreements; and the voluntary carbon market.
• Standards and certification
Policies
Brazilian Forest Code (recent modifications, debate ongoing)
Action Plan for Prevention and Control of the Legal Amazon Deforestation
(PPCDAM) (significantly reduced deforestation rates since 1994)
Credit and subsidies program – National Environment Program, Green Aid,
Protected Areas Fund, Climate Fund, and agricultural policies.
Soy moratorium
Land titling
Land zoning
Food purchase program
Payment for environmental services
Infrastructure for transportation and energy
Climate change plans, including REDD+ in each Amazonian state
Policies
The Brazilian Forest Code: rationale and current status - Created almost 50 years ago, intended to be a tool for
soil/water resources management and for environment protection. In 1996, the government decided to
increase the protected area to 80% of any property in the Amazon. However, compliance to the Forest Code
was not always observed, with implications to forest conservation and agriculture expansion. In an attempt to
minimize the problem, the Congress recently approved many modifications on the Forest Code. To date, the
debate has continued.
Credit and subsidies program - This includes a National Environment Program, Green Aid, Protected Areas Fund, a
Climate Fund, and agricultural policies.
Soy moratorium - Anticipating the possibility that trade barriers could be built against Brazilian exports, ABIOVE
(Brazilian Vegetable Oil Industry Association) and ANEC (Brazilian Grain Exporters Association) decided not to
purchase this grain originated from areas of the Amazon Biome deforested after July 2006.
Land titling - In 2009, the government initiated program with the main objective to promote legal land use by
legitimating previous occupations.
Land zoning
Food purchase program
Payment for environmental services
Infrastructure for transportation and energy - Several main roads traversing the Amazon are in the process of
being paved and increasing accessibility.
Climate change plans, including REDD+ in each Amazonian state
Program for the Acceleration of Development PAC
Action Plan for Prevention and Control of the Legal Amazon Deforestation (PPCDAM) - PPCDAM is an attempt of
Brazil to reduce deforestation of the Brazilian Amazon Forest. Implemented in 2004, it significantly contributed
to the decrease of deforestation rates, discouraging illegal deforestation in Amazon Forest.
Summary of LuccME/BRAmazonia Scenarios – v1 – March, 2013
Primary forest clearcut deforestation
rates
Secondary vegetation
dynamics
Roads
Protected areas (or
Public Forests - UC,
TI, PAE, PDS)
Forest code
enforcement
Scenario A:
Sustainability
Zero deforestation
after 2020
21 to 40% of
deforested area;
regeneration after
2020.
No new federal or
State roads; only
BR163 paved in 2015
2010 network
maintained
After 2014, partial 50%
Scenario B:
Middle of the
Road
2020 deforestation
reduction targets, low
after that
21% of deforested
area, 5 years half life
No new federal or
State roads; all
planned roads paved
in 2015
2010 network
maintained
Not enforced - 20% of
forest area preserved
Scenario C:
Historic
occupation
pattern
Repeating ups and
downs of the past 40
years
21% of deforested All paving and planned After 2020, return to
area, 5 years half life
roads (Federal and
2004 area
State) built
Not enforced - 20% of
forest area preserved
Deforestation rates
Future deforestation rates in each scenario
A (HS/HE)
B (LS/HE)
C (HS/LE)
D (LS/LE)
35000
30000
C and D:
Mirroring past curve
Deforestation (km2yr-1)
25000
20000
15000
10000
B: Voluntary targets until
2020
5000
0
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
A: Zero deforestation after
2020
Quantifiable phenomena that affect
ecosystem services
• Precipitation - crucial to maintain both natural
vegetation and agriculture, replenish rivers and
maintain evapotranspiration
• Recycling of moisture and evapotranspiration
(moisture transport)
• River discharge – navigability/communications
and habitability of river margin people
communities in the region, as well as fisheries
and the vitality of floodplain ecosystems (varzeas)
• Biomass and productivity of vegetation (forests)
- carbon stored and sequestered by the region;
large economic value in terms of timber.
Quantifiable phenomena that affect
ecosystem services
• Agricultural productivity - mainly grass for cattle,
soy beans, a range of newly developed,
sustainably produced cash crops (Açai, Guarana,
etc), palm oil and various regional products
• People migration and economy. Migration can
enhance deforestation but also be a consequence
of a degrading environment
• Land-use change itself affects most of the
variables, as well as being associated with fire
and air quality (smoke and nitrogen emissions).