Cochrane, Mark

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Research Interests: 
Global Climate Change, Fire Ecology, Land Cover Change, Land Cover and Land Use Interactions, Dynamic Systems

Dr. Mark Cochrane conducts interdisciplinary work combining ecology , remote sensing, and other fields of study to provide a landscape perspective of the dynamic processes involved in land-cover change. He is an expert on wildfire, documenting the characteristics, behavior and severe effects of fire in tropical and temperate forests that are inherent to current systems of human land-use and management. His research focuses on understanding spatial patterns, interactions and synergisms between the multiple physical and biological factors that affect ecosystems. Recently published work has emphasized the climate change, human dimensions of land-cover change and the potential for sustainable development. In his ongoing research program, Dr. Cochrane continues to investigate the drivers and effects of disturbance regime changes resulting from various forms of forest degradation, including fire, fragmentation and logging as well as the mitigating effects of forest management. He is currently the principle investigator of over $3.7 million in externally funded research grants designed to quantify fire mitigation effectiveness of billions of dollars of fuel treatment activities across the United States (JFSP), examine climate change and land management effects over the last century on vegetation structure and shifting fire regimes for the United States, Australia and Brazil (NASA), and determine the combined effects of land use change, conservation efforts and forest degradation on biodiversity throughout the Brazilian Amazon (NASA).  He holds a Ph.D. in Ecology from Pennsylvania State University and a S.B. in Environmental Engineering from the Massachusetts Institute of Technology.


Filling a critical gap in Indonesia’s national carbon monitoring, reporting, and verification capabilities for supporting REDD+ activities: Incorporating, quantifying and locating fire emissions from within tropical peat-swamp forests

Project Summary: Because of episodic uncontrolled fires within drained peat-swamp forests, Indonesia is ranked the 4th largest CO2 emitter over the last half century. The former 1 million hectare Mega Rice Project (MRP), designed to convert extensive peat lands into farm lands, is a major emissions source. Deep organic soils storing vast amounts of carbon are now being lost to decomposition and combustion. The 120,000 ha Kalimantan Forests and Climate Partnership (KFCP) Reduced Emissions from Deforestation and forest Degradation (REDD+) project is within the former MRP. In collaboration with the Indonesian government’s Forestry Research and Development Agency (FORDA), we will develop a prototype peat-fire emissions module for KFCP to incorporate into Measuring, Reporting and Verification (MRV) efforts. This capacity will enable annual quantification of fire-related emissions. Our research project will utilize Landsat and MODIS data and products to quantify land cover changes, burned area and estimate the timing of fire activity. We will incorporate TRMM data for relating precipitation history to the timing of observed water table changes that impact peat-fire activity at KFCP. We will integrate satellite data with existing aerial KFCP Lidar (2007 & 2010), and propose a repeat Lidar collection during the study to provide quantified temporal topographic change maps to validate our modeled results of fire-related peat consumption. This project will leverage the extensive and ongoing data collection efforts for hydrology, fuels, land uses and fire occurrence at KFCP, with our initial field work and laboratory testing of regional peat combustion and emission characteristics to provide guided field testing of background and fire-related carbon emission rates and types (e.g. methane, CO2, CO, particulates, other) during El Nino and non-El Nino years as available. Through groundbreaking emissions field sampling of in-situ smoldering surface, shallow (<20 cm) and deep (>20 cm) peat fires, with on-site gas chromatography for quantifying reactive species, whole air sampling for precise lab measurements of non-reactive gases, and simultaneous filter sampling of particulates, we will create comprehensive and pertinent emissions factors (EFs) that will be critically important for assessing the health impacts and total global warming potential (GWP) of these emissions. In our interdisciplinary research, we will investigate the chains of social and bio-physical events leading to these deep-peat fires, integrating fire scene analyses with social data to describe when, where, how, and under what conditions fires within KFCP have occurred, so that more effective mitigation strategies can be developed in the future. Accurate accounting of peat-fire carbon emissions requires understanding how their presence, depth of burning, and spread rates relate to the interplay of climate, weather, land use, land cover, drainage status, disturbance history, fire type, peat depth and composition. Modeling this phenomenon requires defining 1) the annual surface area burned, 2) the available fuel fraction (burnable) at each location through time, and 3) the amount of fuel consumed per unit area. We will implement a modeling approach that initially uses existing data on the peat hydrology, climate, land cover, burned area, timing of ignitions and fuel loads to stochastically provide peat fire probability and parameterize depth and area burned from the 2007 Lidar data. This initial model will be used to project the expected area, type, and depth of burning from 2007-2011 and then checked against the 2011 Lidar data set to refine calibration of the modeled parameters. The third modeling phase will provide Monte Carlo estimates of type, depth and area of burning, with emissions quantitatively weighted by appropriate EFs derived for surface, shallow and deep peat smoke amounts that will be validated using the proposed third Lidar data collection.

Continuation and expansion to a national-scale of the “Filling a critical gap in Indonesia’s national carbon monitoring, reporting, and verification capabilities for supporting REDD+ activities: Incorporating, quantifying and locating fire emissions from within tropical peat-swamp forests” Project

Project Summary: Indonesia ranks as the 3rd largest CO2eq emitting nation, largely due to episodic uncontrolled fires within drained peat-swamp forests. The original project (NNX13AP46G) set out to 1) provide extensive field investigation of land cover, hydrologic, fuel and fire dynamics in a 120,000 ha REDD+ project in Central Kalimantan; 2) Collect a new Lidar dataset to complement our existing 2007 and 2011 coverages; 3) Conduct groundbreaking detailed emissions field sampling of smoldering in-situ peat fires; and 4) Generate a fully parameterized and validated annual emissions model for the study region in support of its REDD+ project. Despite extensive bureaucratic and logistical challenges and delays inherent in working in Indonesia, objectives 1-3 have now been completed and the modeling efforts are ongoing with all necessary data now in hand as we complete the original project time period. However, our recent unprecedented emission findings (Stockwell et al. 2016), gained in situ during the height of the 2015 El Niño, have documented substantial differences between the actual regional peat fire emissions and existing emission factors, indicating regional Indonesian carbon equivalent emissions (100 year) may have been 19% less than current IPCC-based emission factor estimates. The IPCC emission factors are derived from one lab study burning peat from Sumatra (Christian et al. 2003) and considerable variation in emissions may exist between peat fires of Indonesia’s three major peat formations highlighting the need for the additional field emissions measurements we intend to carry out in the continuation of the project proposed here.

We propose expanding to a national level, our successful regional (Kalimantan) CMS project (NNX13AP46G), to better advance Indonesia’s Monitoring, Reporting and Verification (MRV) capabilities for peatland carbon emissions and support nationwide Reducing Emissions from Deforestation and Forest Degradation (REDD) efforts. We will implement our standardized field-based analyses of fuels, hydrology, peat burning characteristics and fire emissions, developed from our ongoing work in a 120,000 ha REDD+ project, to regionally parameterize our peatland emissions model for all of Indonesia’s major peatland areas by including three new locations, Riau and Jambi (Sumatra) and Western Papua (Papua), for inclusion within the Indonesian National Carbon Accounting System (INCAS). We will conduct on-site whole air sampling of natural peat smoke plumes in situ for precise measurement of non-reactive greenhouse gases, collect peat samples just in front of these active peat fires, and burn the samples in the US while measuring aerosol mass and optical properties and reactive gases. This will create comprehensive and pertinent emissions factors (EFs) for each study region that will be critically important for assessing health impacts and total global warming potential (GWP) of these emissions. Remotely sensed land cover/change (Landsat) and surface fire ignition timing and locations (MODIS) provide spatial and temporal drivers for the modelled emissions that will now be validated/constrained at a national level using biomass burning emissions estimations derived from Visible/Infrared Imager and Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) satellite and the new Japanese Geostationary Meteorological Satellite (Himawari-8). Multiple lidar datasets (2014, 2011, 2007) for Kalimantan are being used to quantify model accuracy, and new work will be undertaken to quantify uncertainty in our most recent lidar-based digital terrain model (DTM), further improving assessments of modelling errors.



Map of forests in the Brazilian Amazon which could be designated as National Forests (FLONAS) without conflict with existing conservation lands or human inhabitants

Spatial distribution of fire regimes. Black areas are previously deforested while other colors represent standing forests suffering different levels of fire impact. Forests in red are burning too frequently to persist as tropical evergreen forests and are transitioning to grassland and scrub. Graph shows both cumulative percentage of remaining forests and fire frequency (average return interval in years) as a function of distance from deforested edges in the eastern Amazon.



Last modified: 
Jun 22, 2017