Our Common Future Under Climate Change

International Scientific Conference 7-10 JULY 2015 Paris, France

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Wednesday 8 July - 16:30-18:00 UNESCO Bonvin - ROOM XIII

2215 (b) - Tropical degraded forests response to global change: current knowledge and cross-cutting research challenges for monitoring and processes understanding (Merged with ex-session 2244 - Climate Change Biodiversity and Human Well-Being : illustration from forests and agro-forests systems)

Parallel Session

Lead Convener(s): S. Luque (IRSTEA National Research Institute of Science and Technology for Environment and Agriculture, St-Martin-d’Hères, cedex, France)

Convener(s): P. Sist (Cirad, Montpellier, France), B. Mora (GOFC-GOLD LC Project Office, Wageningen, Netherlands)

16:30

Introduction

B. Mora (GOFC-GOLD LC Project Office, Wageningen, Netherlands)

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Introduction
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16:35

Development of EO based national forest cover monitoring systems in the Congo Basin

C. Sannier (SIRS SAS, Villeneuve d'Ascq, France), L.-V. Fichet, (SIRS SAS, Villeneuve d'Ascq, France)

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Development of EO based national forest cover monitoring systems in the Congo Basin

C. Sannier (1) ; LV. Fichet, (1)
(1) SIRS SAS, Villeneuve d'Ascq, France

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Deforestation is currently known to account for up to 20% of global greenhouse gas (GHG) emissions. Therefore, a significant decrease in deforestation can have a direct positive impact on reducing GHG emissions. Initiatives such as the Reduction of Emissions from Deforestation and Degradation (REDD), Low Emission Development Strategies (LEDS) or Zero Deforestation (ZD) aim to provide incentives to reduce deforestation. The Congo Basin represents the second largest forest area in the world after the Amazon. Deforestation in Congo Basin countries is generally expected to be low. The assessment of forest cover and forest cover change area is essential for the initiatives mentioned above to determine what is referred to as activity data in the Intergovernmental Panel on Climate Change (IPCC) 2006 guidelines on the Agriculture, Forestry and Other Land Use (AFOLU) sector.

Producing estimates of deforestation in tropical countries in relation to greenhouse gas (GHG) emissions often relies on the use of satellite remote sensing in the absence of National Forest Inventories (NFI). A probability sample combined with an appropriate response design can provide forest cover and forest cover change area estimates and their associated uncertainties in the form of confidence intervals at a set probability threshold as required in the IPCC 2006 guidelines and for reporting to the United Nations Framework Convention on Climate Change (UNFCCC). However, wall-to-wall mapping is often required by countries to provide an exhaustive assessment of their forest resources and as input to land use plans for management purposes, but implementing a wall-to-wall approach is expensive requiring specialized equipment and staff. The recent release of the Global Forest Change mapping products could provide an alternative for tropical countries wishing to develop their own wall-to-wall forest monitoring mapping products.

A model assisted regression (MAR) estimator was applied nationally in Gabon and for selected regions in Cameroon and CAR using the combination of both reference data obtained from a probability sample and nationally produced forest cover and forest cover change maps and produced from the Global Forest Change data.  The resulting area estimate is potentially more accurate than the direct expansion estimate and provides an estimate of the precision of the estimate which is not available from the map statistics alone.

Results show that the method presented provides a reliable means of producing forest cover and forest cover change area statistics and confirm the low level of deforestation expected in Congo basin countries. It also confirms the high level of forest cover in Gabon with more than 88% of the country covered by forest covering an area of just over 23.5 million hectares. In Cameroon and CAR, forest represents about 72% of the area of the regions selected with a total of over 5 million hectares.

Forest cover estimates for national level maps lead to coefficients of variation less that 0.3% at national level in Gabon and between 1.4 and 1.8% at regional level in Cameroon and CAR thus reducing significantly the level of uncertainty for forest cover area estimates compared with reference data alone.

Deforestation rates are generally low, with less than 0.4% between 1990 and 2000 in Gabon. In CAR, the deforestation rate is about 1.5% between 1990 and 2000 and 0.8% between 2000 and 2010. However, the deforestation in Gabon is not statistically different from 0 between 2000 and 2010. The same is observed for the Centre region of Cameroon. This is because the changes detected are very small and as a result the coefficients of variations of change estimates are greater.

Overall, results based on the global forest change data are not as accurate and precise and substantial post-processing and calibation are required to obtain results of similar quality than that of the national maps. However, it is considered that the level of effort necessary would be considerably less than that for producing the national maps.

16:45

Will tropical forests face slow down with ongoing climate changes?

M. Aubry-Kientz (Université des Antilles et de la Guyane, Kourou, French Guiana), V. Rossi (Cirad, Yaounde, Cameroon), F. Wagner (National Institute for Space Research, São José dos Campos, Brazil), B. Hérault (Cirad, Kourou, French Guiana)

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Will tropical forests face slow down with ongoing climate changes?

M. Aubry-Kientz (1) ; V. Rossi (2) ; F. Wagner (3) ; B. Hérault (4)
(1) Université des Antilles et de la Guyane, Umr ecofog, Kourou, French Guiana; (2) Cirad, Ur b&sef, Yaounde, Cameroon; (3) National Institute for Space Research, Remote sensing division, São José dos Campos, Brazil; (4) Cirad, UMR EcoFoG, Kourou, French Guiana

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In the context of climate changes, identifying and then predicting the impacts of climatic drivers on tropical forest dynamics is becoming a matter of urgency. We used a coupled model of tropical tree growth and mortality, calibrated with forest dynamic data from the 20 year study site of Paracou, French Guiana, in order to introduce and test a set of climatic variables. Three major climatic drivers of the tropical forest dynamics were identified through the variable selection procedure: drought, water saturation and temperature. Drought decreased annual growth and mortality rates, high precipitation increased mortality rates and high temperature decreased growth. Interactions between key functional traits, stature and climatic variables were investigated, showing best resistance to drought for trees with high wood density and for trees with small current diameters. We then used SELVA, an individual-based model to run forest dynamic simulations for the next century using predictions from the IPCC 5AR with 3 different scenarios corresponding to 3 relative concentration pathways. Basal area, above-ground fresh biomass, quadratic diameter, growth and mortality rates exhibited decreasing values as long as the scenario became pessimistic. Temperature is the strongest driver  highlighting a drop of 40% in average forest growth for the RCP8.5. Our results highlights the potential slow-down danger that tropical forests will face during the next century.

16:55

Exploring causes, risks, and consequences for ecosystem services of tipping points in Latin American forests - the role of biodiversity

J. Verboom (WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, WAGENINGEN, Netherlands), B. Kruijt (Alterra, wageningen UR, Wageningen, Netherlands), C. Von Randow (Instituto Nacional de Pesquisas Espaciais, Sao Jose dos Campos, SP, Brazil), M. Perez Soba (Wageningen University and Research Center, Wageningen, Netherlands), H. Baveco (Wageningen University and Research Center, Wageningen, Netherlands), M. Van Eupen (WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, WAGENINGEN, Netherlands), T. Parr (NERC Centre for Ecology & Hydrology, Lancaster , United Kingdom), K. Thonicke, (Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany), L. Jones (NERC Centre for Ecology & Hydrology, Bangor, United Kingdom), A. Boit (Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany), P. Balvanera (Universidad Nacional Autonoma de Mexico, Morelia, Mexico), E. Leyequien Abarca (Centro de Investigación Científica de Yucatán, Mérida, Mexico), C. Huntingford (CEH, Wallingford, United Kingdom), E. Blyth (NERC Centre for Ecology and Hydrology, Wallingford, United Kingdom), I. Cisowska, (NERC Centre for Ecology and Hydrology, Wallingford, United Kingdom), L. Martorano (s/nº, Belem, Brazil), M. Toledo (Instituto Boliviano de Investigación Forestal, Santa Cruz de la Sierra, Bolivia), M. Pena Claros (WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, WAGENINGEN, Netherlands), B. Purse, (NERC Centre for Ecology and Hydrology, Wallingford, United Kingdom), D. Masante (NERC Centre for Ecology and Hydrology, Wallingford, United Kingdom)

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Exploring causes, risks, and consequences for ecosystem services of tipping points in Latin American forests - the role of biodiversity

J. Verboom (1) ; B. Kruijt (2) ; M. Perez Soba (3) ; H. Baveco (3) ; M. Van Eupen (1) ; C. Von Randow (4) ; T. Parr (5) ; K. Thonicke, (6) ; L. Jones (7) ; A. Boit (6) ; P. Balvanera (8) ; E. Leyequien Abarca (9) ; C. Huntingford (10) ; E. Blyth (11) ; I. Cisowska, (11) ; L. Martorano (12) ; M. Toledo (13) ; B. Purse, (11) ; D. Masante (11) ; M. Pena Claros (14)
(1) WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, Alterra, WAGENINGEN, Netherlands; (2) Alterra, wageningen UR, Wageningen, Netherlands; (3) Wageningen University and Research Center, Alterra, Wageningen, Netherlands; (4) Instituto Nacional de Pesquisas Espaciais, Ccst, Sao Jose dos Campos, SP, Brazil; (5) NERC Centre for Ecology & Hydrology, Monitoring & observation systems, Lancaster , United Kingdom; (6) Potsdam Institute for Climate Impact Research (PIK), Earth system analysis, Potsdam, Germany; (7) NERC Centre for Ecology & Hydrology, Environment centre wales, Bangor, United Kingdom; (8) Universidad Nacional Autonoma de Mexico, Centro de investigaciones en ecosistemas, Morelia, Mexico; (9) Centro de Investigación Científica de Yucatán, Mérida, Mexico; (10) CEH, Wallingford, United Kingdom; (11) NERC Centre for Ecology and Hydrology, Wallingford, United Kingdom; (12) s/nº, Agrometeorology, Belem, Brazil; (13) Instituto Boliviano de Investigación Forestal, Santa Cruz de la Sierra, Bolivia; (14) WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, Forest ecology and forest management group, WAGENINGEN, Netherlands

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This paper presents some key findings from the EU-FP7 funded projects AMAZALERT and ROBIN (Role of Biodiversity in the Climate Change Mitigation), both focusing on the effects of future climate change and land use change on ecosystem services provided by tropical forests in Latin America. New research has demonstrated that a complete dieback of the Amazon rainforest within the 21st century caused by climate change alone is unlikely; however a risk of forest dieback or other forms of irreversible ecosystem degradation on a lower spatial scale still exists. Because of the potentially severe consequences of such ecosystem degradation for the many important services they provide, on various spatial and temporal scales, it is wise to be prepared for the unexpected. Joining the outcome of the two projects, we will present a map of risk of ecosystem degradation, the main factors involved and most useful monitoring and warning mechanisms. We will evaluate the role of biodiversity in degradation as well as its potential to provide critical indicators of ecosystem decline.

Our models show forecasted changes in the biophysical state and the ecosystem services that the environment provides, under future scenarios. These allow us to compare severity of climate change, the influence of socio-economic context, and the implementation of different levels of policy protection of biodiversity and ecosystem services in alternative futures. The models suggest that there may be difficult trade-offs to take into account among ecosystem services, carbon and biodiversity, under these contrasting scenarios.

In combination, climate change (warming, drying, extreme events) and land use change (deforestation, fragmentation) could have a profound effect on the ecosystem, changing carbon cycle, water cycle, nutrient cycle and biodiversity in an irreversible way: from a wet, high biomass high biodiversity system to a much drier low biomass low biodiversity system. As trees and precipitation are bound together in a positive feedback loop (trees cause precipitation, trees need precipitation - in a hydrological cycle with evapotranspiration) and trees and fire in a negative feedback loop (intact rainforest is fireproof, dry forest and savannah are prone to fire causing more tree mortality), the system has multiple steady states and a critical transition from one state to another would be hard to reverse. If and when such degradation would occur, an Early Warning System (EWS) that would detect the imminent change would help to minimise its impacts.

Although earlier work suggested that early warning signals might exist, such that the onset of large scale dieback could be detected and potentially halted before irreversible critical transitions could occur, current work suggests that there is uncertainty whether critical degradation would show any critical ‘tipping point’ behaviour, and whether such change would be associated with detectable early-warning signals, such as enhanced but slowing down variability in variables ahead of thresholds that are associated with the change. Because of this, monitoring for early detection and warning of change is essential, both on the ground and using satellite images, as monitoring is prerequisite for finding solutions and early adaptation. Due to time lags between the system reaching adverse conditions and the response of the system to these adverse conditions (ecosystem degradation) we might be able to reverse the process before it becomes irreversible.

Since much of any critical change would occur through changes in the hydrological cycle, river levels, rainfall amount, soil moisture and temperature range appear among the most important candidates for monitoring, along with biomass, carbon exchange and energy budgets, but monitoring needs may differ according to the specific risk in a subregion. Local communities will be the first to notice subtle change in processes in their home territories, e.g. changes in ecosystem services provision, so combining high tech knowledge like satellite imagery with low tech on the ground observations should be the most promising way forward.

Actions against ecosystem degradation include reforestation, agroforestry production systems without burning, and agricultural no-tillage system.

17:05

Predicting the combined impacts of climate change and selective logging in timber production forests of Central Africa

F. Mortier (Centre for International Cooperation in Agricultural Research for Development (CIRAD), Montpellier, France), F. Claeys (Centre for International Cooperation in Agricultural Research for Development (CIRAD), Montpellier, France), D.-Y. Ouédraogo (University of Liège, Gembloux, Belgium), L. François (University of Liège, Liège, Belgium), S. Gourlet-Fleury (Centre for International Cooperation in Agricultural Research for Development (CIRAD), Montpellier, France), B. Hérault (Guyanese Forest Ecology (ECOFOG), Kourou, France), R. Gaspard (Guyanese Forest Ecology (ECOFOG), Kourou, France), A. Fayolle (University of Liège, Gembloux, Belgium), N. Picard (Centre for International Cooperation in Agricultural Research for Development (CIRAD), Yaounde, Cameroon)

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Predicting the combined impacts of climate change and selective logging in timber production forests of Central Africa

F. Mortier (1) ; F. Claeys (1) ; DY. Ouédraogo (2) ; L. François (3) ; S. Gourlet-Fleury (1) ; B. Hérault (4) ; R. Gaspard (4) ; A. Fayolle (2) ; N. Picard (5)
(1) Centre for International Cooperation in Agricultural Research for Development (CIRAD), Tropical forest goods and ecosystem services (bsef), Montpellier, France; (2) University of Liège, Biosystems engineering (biose), Gembloux, Belgium; (3) University of Liège, Unit for modelling of climate and biogeochemical cycles (umccb), Liège, Belgium; (4) Guyanese Forest Ecology (ECOFOG), Kourou, France; (5) Centre for International Cooperation in Agricultural Research for Development (CIRAD), Tropical forest goods and ecosystem services (bsef), Yaounde, Cameroon

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In the design and the implementation of current rules of Sustainable Forest Management (SFM), still too little account is taken of the sensitivity of tropical forests to climate change. In the Congo Basin, forests cover 220 million hectares and represent an economic sector of utmost importance for the rural development as well as for national and regional climate strategies. Hence, these forests constitute a major challenge for both adaptation and mitigation.

A prerequisite to ensure the relevance and the effectiveness of SFM recommendations in this region is to elucidate the influence on forest dynamics of both climate change and harvesting pressure. This influence will likely consist of major shifts in structure and floristic composition. By opening the stands and increasing light availability, selective logging fosters the development of light demanding species. Some of these species, particularly the pioneers, are thought to be particularly drought sensitive so that global warming could strongly impact logged forests. The study of forest-climate-logging relationships needs therefore species-level predictions. However, the high diversity of tropical forests, in pair with the scarcity of data, hinders the correct fitting of species-specific models.

To investigate the combined effects of climate and harvesting influence on Central African forests, we conducted long-term simulations of forest dynamics under several scenarios of climate change and timber harvesting. Climate scenarios were based on outputs from simulations of the atmospheric model ARPEGE-Climate of the French National Centre for Meteorological Research (CNRM), performed within the Coupled Model Intercomparison Project Phase 5 (CMIP5) and under several Representative Concentration Pathway (RCP) scenarios of the International Panel on Climate Change (IPCC). We also used outputs fields such as soil water and potential evapotranspiration from the model CARbon Assimilation In the Biosphere (CARAIB) of University of Liège obtained under the same climatic scenarios. Logging scenarios were implemented by considering a wide range of felling intensities.

To carry out this work, we developed an innovative method based on a Mixture of inhomogeneous matrix models (MIMM) that permits to test and simulate the influence of timber harvesting and climate change on forest dynamics. While insuring a satisfactory fitting of vital parameters, such a methodology allowed us to reflect the diversity of tree ecological patterns, notably in response to climate variables. To do this, we simultaneously clustered species into groups according to species-specific ecological responses and identified group-specific explicative environmental and climate variables. To infer and validate model outputs, we used the M’Baïki site, in the Central African Republic (CAR), a unique experimental site that has been monitored for 30 years through a collaborative partnership with various French and CAR institutional and research organizations.

Our methodology is a novel tool to accurately predict long-term ecological consequences in Congo Basin forests under both constraints of climate change and selective logging. One of the main immediate applications would be to check if classical SFM strategies, such as Reduced Impact Logging (RIL), Improved Forest Management (IFM) or post-logging sylviculture, are still valid when the ecological complexity and the climate sensitivity of tropical forests are duly taken into account. As an envisaged development, a coupling with a logging company model could allow to predict climate change impact on the economics of forest-based sectors, including tax revenues and socio-economic local benefits. More generally, our work could contribute to the improvement of climate-smart policies for Central African forests, a critical issue in the current context of deployment of the mechanism of Reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+).

17:15

Q&A session and Introduction to the Panel discussion - Key issues

P. Sist (Cirad, Montpellier, France)

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Q&A session and Introduction to the Panel discussion - Key issues
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17:20

Panel Discussion

P. Sist (Cirad, Montpellier, France), B. Mora (GOFC-GOLD LC Project Office, Wageningen, Netherlands), F. M. Seifert (European Space Agency, ESA-ESRIN, Frascati, Italy), J. Verboom (WAGENINGEN UNIVERSITY AND RESEARCH CENTRE, WAGENINGEN, Netherlands), V. Gond (CIRAD, Montpellier, France)

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Panel Discussion
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