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© Fernando Bajaña / Vista aérea CUYABENO/ WWF
Vision
Beyond Borders
Protected Areas
Amazon
Amazon
Vision
Protected Areas
Beyond Borders
© Archivo fotográfico WWF-Colombia
Donors
Vulnerability and climate risk analysis
of the Amazon biome and its protected areas
© WWF ISBN ebook: 979-958-8915-42-5
WWF Colombia Design and layout: Contents
Johanna Prüssmann El Bando Creativo
César Freddy Suárez
Jairo Guerrero Image Credits: Foreword 5
Óscar Guevara
Julia Gorricho Figure 2.
Luis Germán Naranjo Basemap: Esri, DigitalGlobe, Geoeye, Earthstar Geographics, CNES/Airbus DS, Introduction 6
Melissa Abud USDA, USGSm AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Paris Agreement – United Nations Framework Convention
Carolina López Community. Esri, HERE, DeLorme, MapmyIndia, © and the GIS User Community. on Climate Change 7
WWF Brazil Figure 14.
Conceptual and methodological framework 8
Bernardo Caldas de Oliveira Ficus máxima Guerrit Davidse
Mariana Napolitano e Ferreira Ateles belzebuth Pete Oxford Introduction 9
Tetrapus sp Christian Ziegler Methodological framework 9
Tapirus terrestris Guillaume Feuillet Strengths, weaknesses and limiting factors 10
WWF Ecuador – WWF LAC
Pecari tajacu Adrian Hepworth
Analiz Vergara Panthera onca Frans Lanting
Geographic scope of the analysis 11
Bradypus variegatus Adriano G. Chiarello
Meteo-Colombia Amazilia versicolor Nick Athanas Variability and climate change in the Amazon biome 13
Thorsten Beisiegel Ceiba pentandra Steven paton, Smithsonian Tropical
Research Institute
Introduction 14
José Daniel Pabón
Patricia Téllez Phyllostomus discolor Programa de Conservación de los Inter - annual and inter - decadal variability (long term) 14
Murciélagos de Paraguay – PCMPy Climate variability and changes in net forest productivity 15
This publication is the result of Boa constrictor Nicole Hollenstein
Changes in climate variables 16
a collaborative effort between Dasyprocta fuliginosa Ryan Shaw
the national protected areas Cuniculus paca David Cook Temperature 16
institutions of Colombia, Crax globulosa Vla Bulatao Precipitation 17
Ecuador, Bolivia, Brazil, French Myoprocta acouchy Milan Korínek Regional Climate Change Index 18
Guiana, Guyana, Peru, Suriname Cebus albifrons Bruno Salaroli
and Venezuela. Cebus albifrons Francisco Estéves
Mauritia flexuosa www.rarepalmseeds.com Ecosystem Services 19
Editor: Astrocaryum chambira www.beamazon.org Water resources 20
Euterpe precatoria Mateo Hernández
María Elfi Chaves S. Carbon storage 22
Caryocar villosum Renan Chisté
Ara macao parfaitimage.com Biodiversity–Species habitats 23
Editorial coordination: Sarcoramphus papa Alessandro Abdala Ecosystem functionality 24
Carmen Ana Dereix R. Beyond changes in potential species distribution 26
Potential climate refugia 27
August 2016
Landscape transformation drivers 29
Correct citation: Prüssmann J., Suárez C., Guevara O. and A. Vergara. 2016. Vulnerability and Deforestation 30
climate risk analysis of the Amazon biome and its protected areas. Amazon Vision, REDPARQUES,
WWF, UICN, FAO, PNUMA. 48 pp. Cali, Colombia. Forest fires in the Amazon 31
Ecological Risk Index 32
Spanish to English translation: Alexandra Walter.
Denominations in this document and its content do not imply, on the part of participating institu-
tions, any judgment whatsoever on the legal status of any territory or area, or the endorsement or
acceptance of such boundaries or limits.
Integrated Risk Index 34
Protected areas contribution to resilience of the biome 37
Developing the climate resilience concept 38
Basic elements of an agenda focused on climate resilience
Initial components
38
39
Foreword
T
Climate resilience and ability to facilitate change 41
he Amazon is the biome with the greatest area of continuous tropical forest in the world. In
fact, its size is twice that of the second largest watershed, the Congo River. Additionally, it is
Conclusions and Recommendations 42 the most important water system in the Planet, containing almost 20% of the world’s fresh-
Main results of the analysis 43 water. It harbors refugia for hundreds of species and five of the 17 of the world’s mega diverse
countries are in the Amazon. The biome provides critical ecosystem services to humankind, serving as
The role of protected areas 44
climate regulator not only of the region, but also of the Planet; 10% of the world’s carbon is found in
Constructing a regional resilience agenda 45 its forests; and its water cycle guarantees this resource for distant regions through its “flying rivers”
–moist water masses traveling throughout South America, providing this vital liquid to faraway lands.
The Amazon houses more than 30 million inhabitants, including close to 350 indigenous communities
References 46 and cultures.
However, this enormous wealth is particularly vulnerable to the effects of climate change, which are
multiplied by a series of unsustainable activities related to the growth of the agricultural frontier, the
construction of infrastructure and the extraction of non-renewable resources, among other factors.
The current study, conducted by an extraordinary team of professionals, with active participation of
Amazonian governments, provides an analysis, with a regional perspective, of climate vulnerability
and risk in the Amazon and its protected areas. The document indicates, among other things, that fac-
tors related to climate change and land use change will very probably affect the quality and quantity
of ecosystem services provided by the Amazon biome. Studies show that the regions with the highest
climate change risk and the greatest sociocultural vulnerability are those in the eastern Amazon
region, also close to Manaus in Brazil and Iquitos in Peru, as well as in the Colombian and Peruvian
piedmont in the western part of the biome.
An important conclusion of this study is acknowledging the role played by protected areas, as basic
buffer zones of climate change impact on biodiversity and in reducing related risks. The study also
shows that protected areas are important tools for adapting to and mitigating climate change, and
that conservation as a whole is fundamental in reducing vulnerability–very much in line with RED-
PARQUES’ declaration at the Conference of the Parties in Paris in 2015 during the United Nations
Framework Convention on Climate Change. Both protected areas and indigenous territories are fun-
damental to guaranteeing that the Amazon region continues providing its services.
We hope that this study serves as an input in guiding governments and civil society in making deci-
sions on conservation and effective management, enabling Amazonian countries–with support from
the international community–to maintain the ecological functionality and integrity of the biome, and
to develop and implement an agenda of resilience to climate change for this very important region of
our Planet.
TARSICIO GRANIZO PEDRO GAMBOA
Coordinator - Amazonian Coordination Director, National Protected Areas Service,
Unit, WWF LAC SERNANP, Peru – REDPARQUES Regional
Coordinator
Quito and Lima, August 2016
5
Introduction Paris Agreement – United Nations Framework
Convention on Climate Change
R
ecent, detailed, fine-scale data on climate, variability and climate change has not been suf-
ficient to establish how biodiversity, communities and economic sectors will be exposed and In the 21 Conference of the Parties (COP21) of the United Nations Framework Convention on Climate
threatened by climate change or to support decision making at different levels of public policy. Change (UNFCCC), conducted in December 2015, the Parties signed the Paris Agreement, mainly
The international community adopted a conceptual framework and invested important re- because there was an implicit acknowledgement that mitigation and adaptation efforts had been
sources in climate change vulnerability evaluations as the sole indicator, not understanding the need insufficient, and that evidence indicated a progressive increase in magnitude and rate of incidence of
to analyze existing and expected climate risks and variables at different scales and in highly complex anthropogenic activities on global climate.
systems that determine their capacity to withstand and recover from negative impacts.
As a consequence, Article 5 of the Agreement encourages the parties to incentivize and support
Vulnerability and climate risk analyses conducted in the framework of the Amazon Vision and present- conservation, sustainable forest management, increase in carbon forest reserves, and more “alter-
ed in this publication, include other elements in an integrated approach that enabled defining climate native policy approaches, such as joint mitigation and adaptation approaches for the integral and
change adaptation strategies linked to protected areas effectively, and strengthening resilience of sustainable management of forests”. To this end, all local, subnational, national and international
the Amazon biome. Our analyses focus on contributing efforts to the goal of the Latin American management levels are being urgently convened to double efforts at equivalent and relevant scales
Network for Technical Cooperation on National Parks, other Protected Areas, and Wild Flora and to reach an adequate reduction in both greenhouse gas emissions and in climate risk, in synergy with
Fauna (REDPARQUES, from its name in Spanish) of consolidating an Amazon Conservation Vision that development pathways that nurture sustainable development objectives.
acknowledges the importance of the Amazon biome not only for its rich biodiversity but for its supply
of ecosystem services at a local, regional and global scales. The Amazon Conservation Vision plays an important role in this context. Since its inception, after a
process starting in 2008 at the initiative of Amazon countries members of REDPARQUES, efforts have
This document presents the results of the analyzes carried out through a highly collaborative process, tried to mainstream this vision in participatory Amazon biome conservation planning and manage-
in its seven main sections, in addition to this introduction. First, a brief synthesis of the conceptual ment strategies. One of the goals is consolidating representative, complete and effectively managed
and methodological framework used in the analyses; second, a reference to variability and climate protected areas systems in the Amazon. Another goal is learning how to face the most urgent pres-
change in the Amazon biome, including the Regional Climate Change Index. The third section includes sures, threats and change factors, including those derived from climate change, while identifying
analyses of ecosystem services related to water resources, carbon storage and biodiversity, specifi- opportunities to benefit local communities. The initiative is a joint effort of REDPARQUES, institutions
cally in relation to the habitat of different species. The fourth section, dedicated to the main transfor- involved in each country’s national parks, the International Union for the Conservation of Nature
mation drivers, defines the Ecological Risk Index in the Amazon biome; and the two indices mentioned (IUCN), the United Nations Food and Agriculture Organization (FAO) and the World Wildlife Fund
contribute to the Integrated Risk Index presented in the fifth section. The role that protected areas (WWF)–all of which share common objectives and in addition provide the knowledge, resources and
could play in enhancing the biome´s resilience is briefly discussed. Lastly, the conclusions section leadership required to achieve results demanded by the Vision.
summarizes the main results and based on these, presents recommendations for further action to
address climate change adaptation in the Amazon biome. Since 2014, as part of the implementation of the Amazon Conservation Vision, REDPARQUES and
WWF, through the projects SNACC1 and IAPA, have directed efforts to improve understanding of
transformation processes in the Amazon biome originating in or triggered by climate change, of prior-
ity actions for conserving and managing the biome in a “climate-smart” way, and of mechanisms for
strengthening planning and management of protected areas systems.
1 The Amazon Conservation Vision currently has two projects being implemented in the framework of this initiative: 1)
Protected Areas, Natural Solutions to Climate Change (SNACC, from its name in Spanish) – financed by the German
Federal Ministry for Environment, Nature Conservation, Building and Nuclear Safety (BMUB, from its name in German)
and WWF Germany; 2) Integration of Protected Areas in the Amazon biome (IAPA, from its name in Spanish) – financed
by the European Union and FAO.
7
Conceptual and
methodological framework
Introduction Methodological framework
The last report of the Intergovernmental Panel on Climate Change Technical vulnerability and risk studies (Figure 1) are intended to
(IPCC), AR5-2014, states that adaptation to climate change re- provide inputs for strengthening planning and management in
quires an approach in its risk analysis that takes into account protected areas, in a broad context that includes climate man-
interactions between climate, and socio-ecological systems. The agement objectives, such as mitigation, adaptation and resilient
report highlights the need to construct “climate-resilient path- development, and low carbon. Throughout the conceptual design
ways” that, in the case of the Amazon biome, combine climate and execution of the analysis, project partners agreed that tech-
risk reduction and increase in climate resilience to achieve the nical studies would address each of these specific objectives,
objective of conserving a healthy and sustainable Amazon land- which necessarily implies integrating multiple scales, sources of
scape. information, spatial modeling techniques and analyses.
Consequently, the first steps to fulfill this integration goal are re-
Our work seeks to contribute to evaluating climate adaptation lated to technical studies that:
needs in the biome and integrating this evaluation in the Ama-
zon Conservation Vision, based on the following concepts: Focus • Enable understanding both average conditions as well as
on analyzing climate vulnerability and risk and on identifying the variability of historical, current and expected climate in the
sources of ecosystem services and resilience in the biome. We try Amazon biome.
to guarantee the inclusion of critical links between climate (cli-
mate change, variability and extreme climate events) and biodi- • Identify the incidence of potentially dangerous physical phe-
versity (species, ecosystems and ecosystem services), especially nomena and threats trigged by or originating in climate con-
in the context of protected areas. We develop an applied meth- ditions.
odology partially based on the IPCC’s AR5 and other proven tools
which, combined, have aggregated value. This approach gives • Update the baseline of climate, biological, social, economic
flexibility to our analysis in its development both in the context of and institutional data of the Amazon biome.
specific protected areas in the Amazon biome, and in the context
of needs and capacities of each of the countries involved. • Model the biome’s current and future capacity to provide
ecosystem services, regulate water systems, capture and se-
quester carbon and provide habitats for species, under chan-
ging conditions in land use and climate scenarios.
• Analyze and evaluate climate risks, understood as potential
We try to guarantee the inclusion of losses in the biome’s functionality2.
critical links between climate (climate
• Identify biophysical factors of the Amazon biome that are po-
change, variability and extreme tential sources of climate resilience.
climate events) and biodiversity
(species, ecosystems and ecosystem • Support policies and development models required for inter-
© J.J. Huckin / WWF-US services), especially in the context of vening territories with a conservation and social develop-
ment commitment, and that nonetheless are under threat and
protected areas. transformation due to changes in climate conditions to which
they are not adapted.
Conceptual and
methodological framework
2 Functionality understood as the capacity to provide ecosystem services.
9
10 Conceptual and
methodological framework
Climate Understanding climate observed, expected and extreme, and which can Geographic scope Atlantic
Ocean
represent threatening conditions and a change factor for the Amazon
Analysis biome. of the analysis VENEZUELA
GUYANA
SURINAME
FRENCH
The SNACC Project’s technical committee agreed to de- COLOMBIA GUIANA
The Amazon Biome's capacity to provide ecosystem services (carbon limit the study area based on the concept that the Am-
Ecosystem azon biome is a biogeographic area, previously defined
sequestration and capture, water regulation, habitat for species) under
Functionality current conditions and in scenarios of climate and land use changes. by Olson and Dinerstein (1998). The resulting polygon
ECUADOR
covers 6 851 583.24 km2 within the jurisdiction of eight
countries (Bolivia, Brazil, Colombia, Ecuador, Guyana, PERU
Potential impacts originating or triggered by changing climate conditions Peru, Suriname and Venezuela) and an overseas territory
Analysis (climate change, climate variability and extreme events) that may
negatively affect the biome's functionality, and therefore its conservation (French Guiana; Figure 2).
of Climate Risks BRAZIL
and social well-being objectives.
BOLIVIA
Analysis
of Climate
The Amazon biome's capacity for recovering from the progressive impact The Amazon biome covers Pacific
of climate change, or, in other words, the materialization of climate risks.
Resilience 6 851 583.24 km2 within the Ocean
jurisdiction of eight countries
Figure 1. Methodological framework used in the present study. and an overseas territory. 0 500 1,000 km
Amazon Amazon Amazon
biome basin extend
Strengths, weaknesses and limiting factors
This analysis is an important step forward in understanding the On the other hand, during the different discussions and exercise
impacts of climate variability and change in the Amazon biome development processes, the proposal was presented to assign How much area does each country contribute to the Amazon biome?
and its relationship to the protected areas system and ecosystem greater relevance to the social context role of the Amazon in the
services provision. It provides information and key data for deci- vulnerability analysis. However, differences in existing indicators Absolute extension of the Amazon biome by country Relative extension of the Amazon biome by country
sion making at the regional level, as a complement to defining in Amazon countries with regard to their temporality, concepts 4.05
strategies for facing the challenges of global climate change in and measuring methods did not allow us to completely integrate 4 Peru Suriname Venezuela
French Bolivia
Area (million km2)
the Amazon region. The document gathers several studies con- these aspects. 3 Guiana
11.27% 2.35% 6.69% 5.99%
ducted in the region, that provide technical references on dif- 1.34%
ferent themes (hydrology, climate, and physical and biological 2
aspects); we invite the reader to consult these studies which pro- Guyana
1 0.77
vide greater detail and clarity on the technical elements studied. 0.41 0.54
0.24 0.46 3.51%
0.12 0.09 0.16
Little is known on the status of the 0 Ecuador
In spite of the variety of information sources during the revision of 1.75%
vulnerability of species in the face of
Bolivia
Brazil
Colombia
Ecuador
Guyana
French
Guiana
Peru
Suriname
Venezuela
bibliographic and geographic information, large data gaps were
observed, most having to do with scarcity of properly referenced expected impacts in climate variability Colombia Brazil
climate, hydrology and biological data. As is common, there are and change, which became a factor 7.94% 59.17%
biases in favour of areas with greater access. Also, little is known limiting the development of this study.
on the status of the vulnerability of species in the face of expect-
ed impacts in climate variability and change, which became a Figure 2. Limits and figures of the Amazon region. Sources: Esri, DigitalGlobe, Geoeye, Earthstar Geographics, CNES/Airbus DS, USDA, USGSm AEX,
factor limiting the development of this study. Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community. Esri, HERE, DeLorme, MapmyIndia, © and the GIS User Community.
Almost 30% of the Amazon biome (1 945 769 km2), is under some kind of protection IUCN category (Figure 3).
This includes 439 protected areas of all IUCN categories, 11 Ramsar sites, 7 UNESCO Biosphere Reserves and
7 UNESCO World Heritage sites (IUCN and UNEP-WCMC 2015, Ramsar 2015). These areas are the core of
REDPARQUES’ work in building resilience in the Amazon biome to face the negative impacts of climate change.
However, only 145 protected areas, 28% of the protected territory (i.e., 815 764 km2 or 11.9 % of the biome) are
in IUCN’s stricter categories: Ia, Ib and II.
11
12
©
Protected areas sources:
Bolivia, Brazil, Colombia, Ecuador and Perú: Data were given by each
country’s Environmental Ministry.
Venezuela, Guayana, French Guiana y Suriname: IUCN and UNEP-WC-
MC (2015), The World Database on Protected Areas (WDPA) [On-line],
08/2015], Cambridge, UK: UNEP-WCMC. Available at:
www.protectedplanet.net
Percentage of the Amazon biome
under protection in each country
Protected
Peru Suriname Venezuela Bolivia
areas 16.98%
8.75% 1.22% 3.08%
IUCN Category
French
Ia Guiana
Ib 2.57%
ll
lll Guyana
IV 1.07%
V Ecuador
Vl 1.59%
Brazil
Not Colombia
reported 59.19%
5.56%
Number of hectares per country included in protected areas Contribution by each Amazon country
(inside the biome) to the biome´s protected areas system
1,200 1,099.36
300
253
Area (thousand km2)
1,000
250
800
Protected areas
200
600
150
400 315.32
162.42 100
200 103.23
57.14 29.52 19.83 47.77 22.65 38
50 24
0 15 9 5 15 16 13
0
Bolivia
Brazil
Colombia
Ecuador
Guyana
French
Guiana
Peru
Suriname
Venezuela
Bolivia
Brazil
Colombia
Ecuador
Guyana
French
Guiana
Peru
Suriname
Venezuela
© Archivo fotográfico WWF-Colombia
Figure 3. Extension of protected areas in the Amazon biome. Sources: Ministries of the environment of Bolivia, Brazil, Colombia,
Ecuador and Peru. IUCN 2015: Venezuela, Guyana, French Guiana and Suriname.
The borders of the Amazon river watershed do not necessarily
coincide with those of the Amazon biome, which also includes Protected areas are the core of Variability and climate change
areas of other watersheds: Orinoco River in the northeast; Esse- REDPARQUES´ work of strengthening
quibo, Courantyne and Maroni rivers in the north; and Gurupi and
Tocantins rivers in the east. In the Andean zone, in the western resilience of the Amazon biome in order in the Amazon biome
part of the region, the biome does not include the glacial and sub to face the negative impacts of climate
glacial zones in the water divide of the watershed. change.
13
14 Variability and climate change
in the Amazon biome
Introduction Table 1. Climate variability indices in the Amazon biome
Because of its huge size, climatic
Because of its huge size, climatic patterns in the Amazon are af- Sector of the Amazon with the greatest effect.
patterns in the Amazon are affected Regulatory process
fected by extreme climate variability phases and have specific Precipitation Temperature
subregional characteristics (Espinoza et al. 2009). Given the bi- by extreme climate variability
ome’s geographic position and the movement of the inter-tropical phases and have specific subregional Very significant effect in the
Very significant direct positive effect
northwest, north and south of the
convergence zone, the Amazon biome exhibits an annual climatic characteristics (Espinoza et al. 2009). Inter - annual variability
Amazon. Not significant in other
of El Niño and La Niña in the northern
bipolarity, which means that humid and dry months in the north- part of the region.
ern zone are opposite of those in the southern zone. In other areas.
words, when precipitation is low in the northern region, it is high Temperature variability No noticeable effect on
in the southern region, and vice versa. Evident effect on temperature.
in the northern Atlantic precipitation.
Inter - annual and Inter decadal variability Significant inverse effect on the extreme
To determine the degree of influence of global atmospheric
phenomena on climate variability in the Amazon, the relation inter - decadal variability in the Pacific eastern part of the watershed.
No effect.
between precipitation and temperature was analyzed using 10
climate indices available in the database of the Climatic Re-
(long term) Inter decadal variability
in the Atlantic
No effect.
Noticeable inverse effect in the extreme
eastern part of the watershed.
search Unit at 134 stations (CRU 2015, Jones et al. 2012). Analy-
sis of these data showed extreme variations expressed in critical At the regional scale, many of the climate variability indicators
events, such as the 2005 and 2010 droughts and the 2002, 2008 show a much more evident relationship with climatic processes
and 2015 floods. This section discusses results of these analyses in the tropical Pacific than with those in the Atlantic (Figure 4 and Climate variability and changes
and climate change models, using multiannual precipitation and Table 1). The El Niño phenomenon in the Pacific East results in in net forest productivity
temperature averages, with a current reference period and a fu- precipitation deficits in large areas of the Amazon region during
ture scenario equivalent to an RCP of 8.5 for 2030. Longer periods all seasons, especially between December and February (the
austral summer). Air temperature anomalies also have a differ- Extreme climate events also have an effect on the structure and on the capacity of Amazon forests to respond to drought impacts,
were used for the biodiversity analyses: to years 2050 and 2080. functioning of the Amazon forest. The water flow in Amazon for- areas with the greater deficit of soil moisture have a net biomass
Finally, an integrated risk index was generated for the conditions ent spatial distribution, with greater positive values during the
austral summer. ests during the dry periods is regulated mainly by the access of loss during those events (Meir et al. 2009, Phillips et al. 2009). For
of the present century. roots to water in the soil and its redistribution in the forest eco- example, during the 2005 drought, more than 70 million ha of the
system, which involves high rates of transpiration and photosyn- western Amazon basin underwent a severe water deficit (Saatchi
thesis (Malhi et al. 2008). Due to the influence of soil moisture et al. 2013; Figure 5).
El Niño conditions
1.5 12.5
A) B)
12 Average annual precipitation (mm) 8 8
1
Oceanic Niño Index (ONI)
11.5
4 4
0.5 11
0 0
10.5
0 -4
10 -4
-0.5
La Niña conditions
9.5
-8 -8
9
-1 -12 -12
8.5
-18 -18
-1.5 8
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Year -76 -72 -68 -64 -60 -56 -52 -48 -76 -72 -68 -64 -60 -56 -52 -48
ONI Precipitation No 3.0 Slow recovery Fast recovery
forest
Figure 4. Correlation between average accumulated multiannual precipitation and the Oceanic Niño Index.
Figure 5. A) Spatial distribution and severity of the 2005 drought B) Recovery rates (Adapted from Saatchi et al. 2013).
15
16 Variability and climate change
in the Amazon biome
Changes in climate variables Precipitation
The greatest increases can be seen during
Evidence of climate change in the Amazon has been re- the period February to May, with certain hot Modeling shows the effect of the relative position of A) JAN FEB MAR APR 1000
peatedly highlighted by several authors (IPCC 2012, 2013, the Earth with respect to the sun and the rotational an-
spots in the northern region, with increases gle on the oscillation of the Inter Tropical Convergence
Marengo 2009, Valverde and Marengo 2011). Results of 800
simulation modeling for the RCP 8.5 scenario confirm find- close to 2°C and a broad southern sector Zone (ITCZ) along the biome, and its consequences on
ings regarding the increase in temperature in the Amazon where increases are as high as 3.6°C. the presence of mid-year, high-precipitation nuclei to- MAY JUN JUL AUG
600
biome. The increase affects the whole territory and fluctu- wards the north and towards the south early in the year.
ates between 0.3 and 3.0°C. Consequently, there will also The spatial distribution of changes in precipitation each
be an overall increase in the water moisture content. The month between the periods analysed, as well as anom- 400
response of precipitation to climate change in the Ama- alies between both periods (Figures 7A-C), suggest that SEP OCT NOV DIC
A) JAN FEB MAR APR 32 the February-June period would show a marked increase
zon is diverse and differs by regions. One possible cause 200
can be the high percentage of precipitation recycling that in precipitation in the southwest (Bolivian and Peruvian
depends on the water supply and the type of vegetation. 29 Amazon) and in the south and east, while there would be
0
a reduction in precipitation in the north (Colombian and
MAY JUN JUL AUG Venezuelan Amazon). Distribution of changes is inverted
26
during the period July-November, with increases in the B) JAN FEB MAR APR 1000
north and reduction towards the south. November, De-
22 cember and January would experience an increase in the 800
SEP OCT NOV DIC eastern sector, over the delta of the Amazon River in the
19 state of Pará. A marked reduction would take place in the MAY JUN JUL AUG
Results of simulation modeling southern and eastern sectors of the region between Octo-
600
for the RCP 8.5 scenario confirm 1 ber and March. On average, reductions close to 20% can
findings regarding the increase be observed in the southeast and east of the region, and 400
some nuclei of increases close to 20% in the north. Pre-
in temperature in the Amazon JAN FEB MAR APR 32 cipitation increases predominate in the southwest, west
SEP OCT NOV DIC
B) 200
biome. The increase affects the and northwest, with values close to 10%, while the rest of
whole territory and fluctuates 29 the watershed has values between -6% and +6%; in other
0
words, without significant changes (Figure 7C).
between 0.3 and 3.0°C.
MAY JUN JUL AUG
26
C) JAN FEB MAR APR 241
22
157
Temperature SEP OCT NOV DIC
On average, reductions close
19 MAY JUN JUL AUG
Overall, an increase in temperature between 0.3 and 3.0°C
to 20% can be observed in the 73
can be observed when analyzing spatial distribution of av- 1 southeast and east of the region,
erage monthly multitemporal temperature changes for the and some nuclei of increases close -12
current (Figure 6A) and future (Figure 6B) periods, in addi- SEP OCT NOV DIC
tion to differences between the two periods (Figure 6C). C) JAN FEB MAR APR 3.6
to 20% in the north. Precipitation -96
The greatest increases can be seen during the period Feb- increases predominate in the
ruary to May, with certain hot spots in the northern region 0.73
southwest, west and northwest, -180
with increases close to 2°C, and a broad southern sector with values close to 10%.
where increases are as high as 3.6°C. Some southern and MAY JUN JUL AUG
Figure 7. Multiannual monthly average precipitation (mm) for A) Current B) Future
western sectors exhibited reductions in temperature (-0.2 0.28 and C) Differences in multiannual monthly averages for both periods.
y +0.2°C) during the period from June to August, and again
during the period between September and January over a
strip running from the northwest to the east. The distri- SEP OCT NOV DIC -0.18
bution of anomalies among average annual temperatures
shows an overall warming between 0.35 and 1.2°C, with
-2.25
peaks in broad sectors of southern, eastern, northern and
central Amazon.
Figure 6. Multiannual monthly average temperatures (°C) for A) Current B) Future
and C) Differences in multiannual monthly averages for both periods.
1718
Regional Climate Change Index
The Regional Climate Change Index (RCCI; Giorgi & Bi 2005, Gi- and Ecuadorian piedemont, the Atlantic coast in the Guianas, and
orgi 2006), shows how temperature and precipitation changes the state of Maranhão in Brazil are the regions with the least
will be distributed throughout the Amazon biome, taking into influence of climate change in the Amazon. In Bolivia, the prov-
account intrannual temperature and precipitation variability in inces of El Beni and Pando in the east have the greatest climate
comparison with current and future climate periods. To calculate change index. Distribution varies across regions in Peru; however,
these, we used the climate characterization of Malhi et al. (2008) the greatest variability is expected in the frontier with Brazil and
which establishes the dry period for the northern region in De- Bolivia.
cember-February, broadening to include November, March and
April; while June-August would be the dry period for the central
and southern regions, broadening to include May, September and
October. Climate change effects will be greater
in the south eastern zone of the biome,
As stated by Giorgi (2006), the main objective of the RCCI analy-
sis is comparing regions among each other, more than providing in the states of Pará, Mato Grosso and
an absolute measure of change. Thus, climate change effects will Rôndonia.
be greater in the south eastern zone of the biome, in the states
of Pará, Mato Grosso and Rôndonia (Figure 8). The Colombian
High
©
© Brent Stirton / Getty Images WWF
0 500 1,000 km Low
Figure 8. Regional Climate Change Index (RCCI) for the Amazon biome.
Ecosystem
Services20 Ecosystem Services
Water resources A)
Average
B)
Percentual
© water yield
High © changes in
water balance
From a biophysical point of view, the response of the Amazon bi- Even though drought and floods are part of the region’s natural
ome to variability and climate change is not uniform at all (Figure variability (have occurred in the past and will continue to happen 100
October 2015 (Telesur 2015, Figure 9A). In February of the same droughts will continue to increase in 0 500 1,000 km 0 500 1,000 km
year, the municipalities of Brasileia and Epitãciolandia in Brazil
and Cobija in Bolivia were flooded (Figure 9B), with great subse-
the future with higher frequency and Low
quent shore erosion processes (Globo 2015, Sol de Pando 2015). magnitude.
C) D)
Changes
© in water
productivity
© Amazon
basin
A) B) (%)
Percentual
100
50 – 200
© Altino Machado.
0 500 1,000 km
200 – 379
Figure 10. A) Average water yield for current conditions. B) Percentual changes in water balance between 2000 and 2005 (anomalies during El Niño).
C) Changes in water productivity in the period 2000 – 2010 (anomalies during La Niña). D) Expected percentual changes in the future average
Figure 9. A) Drought caused serious navigation problems in areas surrounding Manaus in October 2015.
water yield under a RCP 8,5 scenario for sub-watersheds.
B) Extension of the flood of the Acre River in February 2015. Source: http://acrefeijonew.blogspot.com.co/2015/02/tragedia-na-regiao-mais-desmatada.
html. 100
90
% of protected area within watershed
Hydrological modelling using NatCap’s InVEST model (Skansi et al. On the other hand, when comparing the percent- 80
2013) shows that even though, on average, no drastic change in age of protected areas in each of the subwater-
On average, no drastic change in water water yields is expected in future scenarios in the Amazon water- sheds in terms of the effect of climate variability 70
yields is expected in future scenarios shed, drastic changes are actually observed in some watersheds on water yield during the 2005 drought, we ob-
60
in the region (Figure 10), with differences ranging from 0.78% serve that the most extreme variations in terms
in the Amazon watershed, drastic to 50.17% below the average for the reference period and from of water resources take place in basins with the 50
changes are actually observed in some 0.18% to 295.47% above this average. The greatest reduction least territory in protected areas, highlighting the
watersheds in the region. in water yields (39% and 50%) will be in the watersheds of the importance of protected areas in mitigating the 40
Caroni, Caura and Cushabatay rivers, and those with the greatest effects of climate variability (Figure 11). 30
increase (36% and 295%) will be in the watersheds of the Amapá
Grande – Macar and Caño Mono rivers. Figure 11. The role of protected areas on water regulation. 20
10
0
-100% -75% -50% -25% 0% +25% +50% +75% +100%
Water yield variability percentage in 2005
in comparison to the reference period 2001-2010
2122 Ecosystem Services
Carbon storage However, using the HadGEM2-ES climate model of the Hadley
Centre in Great Britain (Collins et al. 2011) and the RCP 8.5
a lesser degree, in the piedmont of Peru and Ecuador. A slight
increase in stored weighted carbon could take place in the central
scenario of carbon emissions, a decrease in carbon content zone of the Amazon.
Undoubtedly, one of the most important ecosystem services provided by the Amazon biome at a global scale is carbon is predicted in three quaters of the Amazon. Until 2030 more
storage, regulating in a great manner our planet’s climate. As shown in the map (Figure 12A - Baccini et al., 2012), than 60% of the area will undergo negative changes in carbon
content up to 8%. Nonetheless, it is important to highlight
carbon density in tropical areas, forests in the Amazon biome store 166,256.61 megatons of carbon, which correspond
that information is limited due to the spatial resolution of the A decrease in carbon content is
to 56.2% of all carbon stored by forest aboveground biomass in the world (FAO 2015). Furthermore, the amount stored
per hectare in protected areas is much greater than in non-protected areas in all countries, being Colombia and Peru atmospheric model. When calculating average multiannual, predicted in three quaters of the
the countries with the highest carbon storage values (Figures 12B y C). annual and monthly variations between the current and the future Amazon.
periods (Figure 13), the greatest weighted carbon losses could
happen in the eastern and southern zones of the biome and, to
2
A) B) © 1
Weighted carbon content by area in aerial
© biomass by country
0
300 -1
280.61 275.28
253.26 245.65 244.56 263.86
246.42
Stored carbon (mg/ha)
236.11 -2
208.91
200
-3
-4
100
-5
0 -6 Figure 13.
Bolivia
Brazil
Colombia
Ecuador
Guyana
French
Guiana
Peru
Suriname
Venezuela
-7 Percentual changes in carbon
content of aerial biomass
0 500 1 000 km throughout the Amazon biome.
C) 0 500 1,000 km -8
Weighted carbon content by area in aerial
biomass within protected areas by country
300 280.63 288.36
256.73 264.34
240.02
265.85 264.50
252.20 Biodiversity–Species habitats
Stored carbon (mg/ha)
422 338 253 169 84 0 277.93
©
200 Almost 40% of tropical rain forests of the world are found in the
Amazon. These neotropical forests are presumed to be the rich-
est in species (Gentry 1988). One very outstanding fact is that a The Amazon biome is the habitat for
Figure 12. 100 hectare of Amazon forest can host 200 to 300 different species approximately 40000 species of plants,
of trees, more than are known in all the European Union. The
A) Magnitude of carbon stored in the Amazon biome (mg/ha). B) Amount of
Amazon biome is the habitat for approximately 40000 species of
427 of mammals, 1294 of birds, 378 of
weighted carbon stored in the Amazon biome, by country. C) Amount of weighted
0 plants, 427 of mammals, 1294 of birds, 378 of reptiles, 427 of am- reptiles, 427 of amphibians and 3000
carbon stored in protected areas. (Source: Baccini et al. 2012).
phibians and 3000 species of fish (Silva et al. 2005, Mittermeier species of fish.
Bolivia
Brazil
Colombia
Ecuador
Guyana
French
Guiana
Peru
Suriname
Venezuela
et al. 2002, 2003).
We evaluated the impact on the distribution of representative
species with different functional attributes in the Amazon biome, W/m² (Hijmans et al. 2005). We also used data on changes in
assuming that the ecological integrity of protected areas depends species distribution generated by the Wallace Initiative (Warren
on maintaining ecological relationships among their conservation et al. 2013), which in turn used bioclimatic variables and optimi-
objects. For our analysis, we used both current and future global zation algorithms of the species’ climate niche to model potential
bioclimatic data, based on a trajectory of RCP emissions of 8.5 future climate refugia (MaxEnt, Phillips et al. 2006).
2324 Ecosystem Services
Ecosystem functionality
King Vulture
Greater Yellow-headed
Sarcoramphus papa
Unlike most current modeling studies, the main criteria for select- Vulture
Scavenger Jaguar Boa
ing species to be modeled in the Amazon biome in this study was Dasyprocta fuliginosa
Panthera onca Boa constrictor Scavenger
the existence of interspecific ecological relations, supported by LC Predator Predator Brown-throated Sloth
scientific information and with sufficient georeferenced records Bradypus variegatus
available in the database needed to feed the modeling exercise. Frugivore LC
Black Agouti Wattled Curassow
Thus, most species presented in the analysis interact with other NT Dasyprocta fuliginosa
species included in the list in one manner or the other. To verify Crax globulosa
White-bellied Frugivore Spotted Paca Frugivore LC
interspecific relations, we consulted scientific articles and books Spider Monkey Cuniculus paca
that mentioned the existence of these interactions. We also took Ateles belzebuth
LC Frugivore
into account other criteria such as their IUCN category of threat, Frugivore EN
if they had been previously selected as conservation objects,
their sensitivity to climatic factors, and their contribution to con- LC
EN
nectivity and supply of ecosystem services.
Scarlet Macaw Versicolored Emerald
Ara macao Amazilia versicolor
Therefore, we generated a simplified network of hypothetical Frugivore Lowland Tapir Frugivore
relations (Figure 14) made up of several trophic levels, links be- Tapirus terrestris White-Fronted Pale Spear-nosed Bat
tween ecological functionality and supply of ecosystem services Capuchin Phyllostomus discolor
LC Frugivore Red Acouchi
generated by the species, which were key for maintaining the Cebus albifrons Margarita Island Pollinator LC
biome’s integrity. In spite of constituting a minimum sample of Collared Peccary Frugivore Myoprocta acouchy Capuchin
VU Pecari tajacu Frugivore Sapajus aplela LC
biodiversity in the Amazon, the analysis of changes in species
distribution is a step forward in understanding the possible future Omnivore Frugivore
LC
impacts on interspecific relations resulting from the change in LC
climatic conditions. LC
LC
Ecosystem Services
Provision
Support
Chambirá Asaí
In spite of constituting a minimum Wasp Rubber plant
Moriche Palm Astrocaryum chambira Euterpe precatoria
Kapok Regulation
Ficus maxima Ceiba pentandra
sample of biodiversity in the Amazon, Tetrapus sp.
Producer Mauritia flexuosa Producer Producer Pequiá Cultural value
Pollinator Producer Producer
the analysis of changes in species Caryocar villosum
Producer
distribution is a step forward in Threat Category
understanding the possible future EN Endangered - EN
impacts on interspecific relations VU Vulnerable - VU
resulting from the change in climatic NT Near Threatened - NT
conditions. LC Least Concern - LC
Figure 14. Network of relations between species analyzed and ecosystem
services.
At the base of this network, are species with an important value The network also includes a set of frugivorous, omnivorous and nectivorous species that depend, in a greater or
for the structure, function and supply of ecosystem services in lesser degree, on the plant species mentioned above (Castro-Vásquez et al. 2010, Galetti et al. 2001, Montenegro
the Amazon forest, and which we have therefore considered to
At the base of this network are 2005) and which contribute as seed dispersers and regulators. Additionally, they represent a source of food for hu-
be cornerstones in this study. At the base of the production chain, species with an important value for man communities and for carnivorous and scavengers in the biome (Fragoso et al. 2003, Pozo 2004, Instituto Sinchi
plant species–most of them associated with ecological succession the structure, function and supply of 2007), which in turn contribute to controlling other populations, including disease vectors. It is worth highlighting
processes–provide habitat, food and diverse benefits to more than ecosystem services in the Amazon that, in addition to the already mentioned ecosystem services provided by this set of species in the biome, several
20 species, including human communities (Lemes & Gribel 2007, species are considered to have important cultural and religious values, such as the jaguar, the boa, and the scarlet
Castro-Vásquez et al. 2010, Nazareno et al. 2007, Instituto Sinchi forest. macaw, among others (Aranda 1994, Hilty & Brown 2001, Wallace & Stanley 1987, Renjifo et al. 2002).
2007, Parolín 2002).
2526 Ecosystem Services
Beyond changes in potential The analysis also shows that new areas apt for the presence of
species distribution different species could arise (climate refugia). These zones need
to be considered carefully since their existence in the future does
not necessarily imply that they will be colonized, particularly
Modeling results show that changes in precipitation regimes during dry seasons, together with temperature by plant species, whose mobility depends on their dispersion
an precipitation seasonality, affect the distribution of species selected for the analysis (Figure 15). The results dynamics and strategies, the presence of appropriate edaphic,
showed that the distribution of species is very sensitive to the increase in frequency and magnitude of extreme luminosity and humidity factors for their physiological needs, as
temperature and precipitation events. Also, the selected species proved to be highly dependent on the distribution well as recruitment of plantlets in new locations, among other
of natural vegetation coverage. factors. As mentioned by the IPCC (2014), plants, in comparison
to other taxa such as mammals or insects, are expected to have a
lower rate of displacement and colonization of new areas under
30 18.31 climate change conditions. Considering the importance of plant
25 species in the trophic networks of a biome such as the Amazon, it
is possible that the diverse species that depend on food sources
20 provided by plants remain in the same zones linked to the slow
Average explanation
11.43 10.57 10.67
10.40 9.03
colonization process of their source of food, even if they have
15
new climate niches available.
of models (%)
10 4.72
2.70 1.88 3.35 According to the analyses, all cornerstone species will proba- © Y.-J. Rey-Millet / WWF-Canon
5 2.54 2.20 2.44 3.03 2.22
1.34
0.93 1.13 0.75 bly lose area of their current climate niche, being thus forced to
0.42 change their distribution and placing their associated interspecif-
0
ic relations at risk. On the other hand, the potential area loss in
Potential climate refugia
Max Temperature of Warmest Month
Min Temperature of Coldest Month
Mean Temperature of Wettest Quarter
Temperature Annual Range
Mean Temperature of Warmest Quarter
Precipitation Seasonality
Mean Diurnal Range
Mean Temperature of Driest Quarter
Temperature Seasonality
Isothermality
Landcover
Mean Temperature of Coldest Quarter
Annual Precipitation
Precipitation of Wettest Month
Precipitation of Driest Month
Precipitation of Wettest Quarter
Precipitation of Driest Quarter
Precipitation of Warmest Quarter
Precipitation of Coldest Quarter
Annual Mean Temperature
the future for highly threatened species will probably be a factor
that will further increase this condition. Furthermore, according
to the analysis, the more generalist species will have a greater In order to complement the analysis of potential future species
extension of climatically stable areas in the future, which hypo- distribution areas, we used data provided by the Wallace Initia-
thetically implies that these species have a greater capacity of tive, which conducted a global analysis of shifts in range by cli-
adapting to expected changes in their climate niche. mate of common and broadly distributed species (Warren et al.
2013). For the data analysis, a species distribution scenario with
When analyzing expected changes within protected areas, no ho- zero displacement was used–meaning that organisms are not
mogeneous behavior is observed in terms of maintaining species able to move and colonize new areas. We used 21 global circula-
richness of the selected groups, indicating that currently estab- tion models that analyzed as a whole groups of species of plants,
Current environmental variables lished protected areas in the biome do not necessarily guarantee amphibians, reptiles, birds and mammals. Taking into account the
mitigation of climate change impacts on species studied. Bearing increasing rate of greenhouse gas emissions and their influence
Figure 15. Averages and standard deviation of each environment variable based on the average percentage of explanation of this in mind, in order to facilitate adaptation processes of biodi- on the climate base line, we used the worst case scenario of
models of the selected species. versity and to maintain the ecosystem services supplied by said future emissions for describing results.
biodiversity, new conservation areas have to be created, and
0 Based on the information on the selected species, strategies to increase connectivity habitats implemented within For each group of species, we determined potential climate refu-
© we analyzed the number of existing relations for the Amazon biome gia–defined as those with sufficient climate stability to maintain
more than 75% of the species modelled, based on the number of
both current and future periods. The percentual
-20 differences indicates losses in interspecific relations global circulation models used by Warren et al. (2013), on a scale
of the Amazon system and the ecosystem services of 0 to 21 (Figure 17). It is worth highlighting the few potential re-
within the hypothetical network (Figure 16). The analysis also shows that new fugia for amphibians and plants (Figures 17 A and D, respective-
-40
areas apt for the presence of different ly), while birds and reptiles could find refugia in several places in
the Andean zone (Figures 17 B and E) as temperature conditions
species could arise (climate refugia). change along the altitudinal gradient, as well as in several zones
Figure 16. in the center of the Amazon region.
-60
Zones of loss of relations among species (% relations lost).
-80
0 500 1,000 km -100
2728
0
Number of
A) Amphibians © B) 1
2
Birds © global climate
models that
3
4
indicate
5
potential
6
refugia
7
8
9
0
10
1
11
12
2
13
14
3
15
16 4
17
18 5
19
20
6
0 500 1,000 km 21
0 500 1,000 km 7
8
9
C) D)
Mammals © Plants © 10
11
12
13
14
15
16
17
18
19
20
0 500 1,000 km 0 500 1,000 km 21
Modelling of the future climate niche shows a difference of 9.3%
for the best case scenario and of 3.2% for the worst case scenario,
E) Reptiles © between the percentage of species that will maintain their climate
niche, both in the current system of protected areas and in the entire
biome (Table 2).
© Michel Roggo / WWF
Table 2. Percentage of species estimated
to maintain their niche in best and
worst case climate change scenarios
Best case scenario Worst case scenario
Biome Protected Biome Protected
areas areas
Amphibians 53 64.0 26 30.1 Landscape
Reptiles 65 73.3 38 42.6
0 500 1,000 km
Birds
Plants
63
57
71.0
67.1
36
31
37.8
33.2
transformation drivers
Figure 17. Climate refugia. Mammals 64 72.8 37 40.6
These results indicate that protected areas do exhibit a slight trend to maintain a greater number of species in the
context of climate change in comparison to the biome.30 Landscape
transformation drivers
Deforestation Deforestation in protected areas (Table 3) is very low in comparison to that of the biome, but slightly greater than
in indigenous territories (RAISG 2015, WWF 2016). It also shows that most deforestation in the Guianas took place
in the last 3 years (2010-2013).
In the year 2000, the forested area in the Amazon biome was close to
5.75 million km2 while deforested area was 492 095 km2, or 8.55%.
The percentage of deforested area for the 2000-2013 period increased During the 2000-2013 period, an
Table 3. Deforestation data within the protected areas system
by 4.92%, representing an additional 269 970 km2 of forest lost by area equivalent to the size of the
in the Amazon biome
2013 (Figure 18). In other words, during the 2000-2013 period, an area United Kingdom was deforested.
equivalent to the size of the United Kingdom was deforested.
Total area deforested (%)
Total number of protected Total area deforested (%)- for the 2000-2013 period,
País areas studied Historic deforestation happening between
2010 and 2013
Bolivia 47 3.80% 20%
© Brazil
Colombia
Ecuador
247
30
17
3.60%
1.50%
5.60%
9%
18%
14%
French
15 0.70% 67%
Guiana
Guyana 6 0.50% 83%
Peru 45 1.00% 13%
Forest
Suriname 13 0.90% 62%
Venezuela 19 2.50% 29%
No forest
Total 439
Water bodies
Average
Deforestation 2.95% 12%
before 2000 value
Deforestation
2000 - 2005
Deforestation
2005 - 2010
Deforestation
2010 - 2013
Forest fires in the Amazon
Figure 18. Deforestation in the Amazon biome during several time periods.
Climate variability has a direct effect on forest fires in the Am- roads connecting the Brazilian Amazon to the rest of the country
azon, due to already mentioned changes in precipitation and opened colonization fronts. This network drove changes in for-
temperature, and indirectly due to resulting changes in the veg- est fires since slash and burn practices were commonly used to
At a regional level for the 2000-2013 period, average deforestation 40,000 etation’s composition and structure (Cochrane & Barber 2009, establish and maintain large areas dedicated to agriculture and
was 20 767 km2 per year. This is equivalent to deforesting every year
35,000 33,873 Pausas & Bradstock 2007). Consequently, large forest fires in the pastures in zones neighboring the road network. The increase in
an area twice the size of the National Amazon Park in Brazil or the
deforestation rate (ha)
Amazon are conditioned by large-scale climate variability, with density of forest fires for the 2001-2005 period is concentrated in
National Yasuní Park in Ecuador. 30,000
events such as El Niño (Figure 5A; Cochrane et al. 1999, UNEP Brazil, in the south eastern part of the biome, where frequency is
Average annual
25,000 2002, Alencar et al. 2006). Nonetheless, dry periods and forest
From a regional perspective, the annual rate of deforestation has been highly correlated with the austral summer; and in the Colombian
20,000 fires, such as those in south eastern Amazon in 2005, were not piedmont, the Beni region in Bolivia and the Pucallpa region in
diminishing in recent years (Figure 19). Because Brazil has such a large
15,000 14,045 necessarily linked to the El Niño phenomenon (IPCC 2007, Figure Peru were the main deforestation fronts (Figure 20B).
share of the biome, actions in this country significantly affect data and
10,126 20A).
regional statistics. Thus, for the 2000-2013 period, annual average de- 10,000
forestation rate was reduced by 50%. However, the opposite situation Fires with the greatest magnitude during the 2000-2014 refer-
5,000 Current fire patterns are undoubtedly different from historic pat- enced period in the biome took place in August and September
was true for the remaining Amazon countries where an increase was
0 terns, as a consequence of human activity. Changes in frequency, 2010. The severe effects generated by these fires were captured
observed in annual average deforestation rate in Bolivia, the Guianas, 2000-2005 2005-2010 2010-2013 intensity and location are dramatic since the decade of 1970’s by satellite sensors, showing severe effects mainly in Brazil,
Peru and Venezuela.
(Cochrane & Barber 2009), when construction of a network of south of the Pará region and north of Mato Grosso (Figure 21).
Figure 19. Average annual deforestation rate in the Amazon biome.
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