Date and Venue
Date: 11-13 November 2019
Venue: Instituto Nacional de Pesquisas da Amazônia (INPA)
Av. André Araújo, 2936, Aleixo, CEP 69060-001, Manaus – AM
Pervasive regions of the humid tropics have been degraded by human activity through selective logging, understory fires, and habitat fragmentation. Consequences of forest degradation range from loss of carbon stocks to loss of biodiversity leaving forests and the communities dependent on them vulnerable to climatic extremes (Aragão et al., 2018; Pinho et al., 2015). Globally, tropical deforestation and forest degradation impacts the ecosystem services (e.g, biodiversity, water, and climate regulation) that support the livelihoods of 1.6 billion people including communities that are among the world’s poorest and most vulnerable (Adger et al 2014; IUCN, 2017; Roy et al 2018). While measuring deforestation using satellite-based estimates of land cover change is relatively straight forward, these same strategies for quantifying forest degradation are limited in their ability to capture more subtle changes in the ecosystem structure and biomass loss associated with degraded tropical forests (Hansen et al., 2013). However, recent estimates of disturbance and degradation suggest that these processes are a significant component (~69%) of the total carbon lost from tropical regions (Baccini et al., 2017). Accurate attribution of natural versus anthropogenic losses and their effects on different carbon pools through modeling is critical to support robust decision-making to avoid further loss and restore already degraded forest (Hurtt et al., 2019). As forest degradation processes are driven by socioeconomic and political decisions, understanding both the history and future of these decisions on forest integrity is critical for populations directly dependent on the forest for their livelihoods and regional economies (Leach & Fairhead 2016). Recent advancements in measuring and modeling global vegetation are encouraging for quantifying and understanding the mechanistic processes of forest degradation. New satellite missions that use lidar and synthetic aperture radar (SAR) technologies will provide data on ecosystem structure at a spatial scale and resolution useful for benchmarking global model estimates of degradation including ESAs BIOMASS, NASAs current GEDI and planned NISAR missions, and DLRs Tandem-L mission concept, and recent model developments can provide more detailed representation of 3D vegetation structure and dynamics (Fisher et al., 2017). In consideration of these advancements, we will also discuss how to better represent socio-economic and political inequalities that act as drivers of forest degradation through scenarios and future trajectories to support decision-making processes as the ecological integrity of forests directly benefits human wellbeing (Agrawal et al., 2018; Rodrigues et al., 2009). Therefore the timing is critical to meet as a cross disciplinary community to develop a method for quantifying forest degradation in order to directly incorporate the mechanistic processes of degradation in models, accounting for the drivers of changes, ecosystem services, biodiversity and livelihood dimensions, thereby providing robust predictions of future climate change impacts over tropical areas. Such a multidisciplinary perspective will greatly advance scientific knowledge in the areas of modeling and observations and will provide relevant information to decision makers for their climate and biodiversity agendas contributing to broader socio-ecological systems security.
Approach and Goals
The workshop will be structured around four objectives:
1. Bring together experts in land use and ecosystem modeling, field ecology, remote sensing, and social science to leverage the expertise, promote synergies among research communities and develop a formal strategy for better integration of observing, monitoring and modeling tropical forest degradation and its impacts in livelihoods regional sustainability under a changing climate and from a multi-scale perspective.
2. Highlight current strategies and approaches for measuring and modeling forest degradation to identify observational strategies, model development, and associated challenges that limit current capabilities.
3. Reflect on how remote sensing is an effective instrument to help reduce climate change risks to socio-ecological systems associated with forest degradation.
4. Identify new initiatives and collaborations to advance the understanding of forest degradation processes and reduce the impacts and risks to livelihoods and sustainability in tropical regions. This workshop will address the above issues and develop a roadmap for future progress in this area for the preparation and publication of an interdisciplinary commentary or perspective article. In addition, a brief summary for decision makers on the discussions and conclusions obtained in the workshop will be produced, as well as the establishment of a community focused on the integration of new strategies for observation and modeling of forest degradation in the tropical region.
The meeting will be organized by a scientific steering committee led by the Future Earth global research project Analysis, Integration and Modeling of the Earth System (AIMES) and participation will be primarily by invitation. The meeting will be open to a small number of other participants (~30). David Lapola, Luiz Aragão, and Patricia Pinho will lead the workshop and help organize the writing efforts that follow.
The workshop will take place over three days. Day 1 will be in plenary mode, with an introductory talk describing goals of the workshop and paper, an overview on the concept of forest degradation spanning perspectives from the field, to mapping degradation using remote sensing, to modeling these processes, to the human dimension of land use change and the effects on ecosystems services and human wellbeing. The morning of Day 2 will be in breakout groups for discussion, initial synthesis, and identification of future research objectives. In the afternoon the groups will finish their summaries and report back in plenary session, followed by discussion and synthesis, including presentation of a suggested outline for the paper that will be produced by the group.
On Day 3 we will take a fieldtrip to visit the ZF2 research station in the rainforest nearby Manaus for an opportunity to experience the world’s largest tropical forest in a scientific context. We will be able to see some long-standing research carried out there at the site (such as the LBA flux tower site) and some newer projects like the CO2 enrichment experiment AmazonFACE.
Scientific steering committee
David Lapola (University of Campinas, Brazil)
Patricia Pinho (Stockholm Resilience Centre, Sweden;UNDP, Brazil)
Luiz Aragão (INPE, Brazil)
Julia Pongratz (University of Munich, Germany)
Natasha MacBean (University of Indiana, USA)
Adger, N., Pulhin, J., Barnett, J., Dabelko, G., Hovelsrud, G., Levy, M., Oswald Spring, Ú., Vogel, C., Adams, H., Hodbod, J., 2014. Human security. In: Field, C.B., Barros, V.R., Dokken, D.J., Mach, K.J., Mastrandrea, M.D., Bilir, T.E., Chatterjee, M., Ebi, K. L., Estrada, Y.O., Genova, R.C., Girma, B., Kissel, E.S., Levy, A.N., MacCracken, S., Mastrandrea, P.R., White, L.L. (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel of Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 755–791.
Agrawal, A., Hajjar, R., Liao, C., Rasmussen, L. V., & Watkins, C. (2018). Editorial overview: Forest governance interventions for sustainability through information, incentives, and institutions. Current Opinion in Environmental Sustainability, 32, A1–A7. https://doi.org/10.1016/j.cosust.2018.08.002
Aragão, L. E. O. C., Anderson, L. O., Fonseca, M. G., Rosan, T. M., Vedovato, L. B., Wagner, F. H., et al. (2018). 21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions. Nature Communications, 9(1). https://doi.org/10.1038/s41467-017-02771-y
Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., & Houghton, R. A. (2017). Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science, 358(6360), 230–234. https://doi.org/10.1126/science.aam5962
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., et al. (2017). Vegetation demographics in Earth System Models: A review of progress and priorities. Global Change Biology, 1–20. https://doi.org/10.1111/gcb.13910
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., et al. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342(6160), 850–853. https://doi.org/10.1126/science.1244693
Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., et al. (2019). Beyond MRV: high-resolution forest carbon modeling for climate mitigation planning over Maryland, USA. Environmental Research Letters, 14(4), 045013. https://doi.org/10.1088/1748-9326/ab0bbe
Pinho, P. F., Marengo, J. A., & Smith, M. S. (2015). Complex socio-ecological dynamics driven by extreme events in the Amazon. Regional Environmental Change, 15(4), 643–655. https://doi.org/10.1007/s10113-014-0659-z
Rodrigues, A. S. L., Ewers, R. M., Parry, L., Souza, C., Verissimo, A., & Balmford, A. (2009). Boom-and-Bust Development Patterns Across the Amazon Deforestation Frontier. Science, 324(5933), 1435–1437. https://doi.org/10.1126/science.1174002
Roy J, Tschakert P, Waisman H, Halim SA, Antwi-Agyei P, Dasgupta P, Hayward B, Kanninen M, Liverman D, Okereke C, Pinho PF, Riahi K, Rodriguez AGS (2018) Sustainable Development, Poverty Eradication and Reducing Inequalities. IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development. pp 435–558.