Biophysical and anthropogenic contributions to fire disturbance dynamics on the peat-swamp landscape, Indonesia

Fires have been increasing in size and frequency across the tropics in recent decades, particularly in tropical peatland areas. Indonesia has the largest amount of tropical peat carbon globally. Fires in fuel-rich tropical peatlands are a major source of carbon emissions, have serious consequences for human health, destroy or degrade habitat, and result in high economic costs. There have been many calls for a better understanding of the relative contributions of the biophysical and anthropogenic factors that drive fire, as this understanding would contribute to the success of efforts to reduce these fires. This dissertation uses remote sensing, fieldwork, and modeling to explore the dynamics of fire disturbance in Indonesia and investigates this disturbance from the framework of coupled human and natural systems, where complex interactions between the social and the biophysical are explicitly considered. Chapters One and Two assess both the influence of various human and biophysical factors to fire probability (Chapter One) and ignitions (Chapter Two) on a peat-swamp forest area in Central Kalimantan, Indonesia, equivalent to a third of Kalimantan's peatland area. A Bayesian modeling approach is used in Chapter One to estimate the effects of atmospheric dryness, human access, vegetation, and hydrology on the probability of fire occurrence. The potential for peatland restoration to offset the impacts of climate on fire occurrence is also explored. I find that climate is the most important factor driving fire occurrence, which is consistent with the findings in many other parts of the tropics. However, two human-driven factors are almost as significant as the influence of climate: drainage canals, which were put in place as part of a failed agricultural project and have lowered the water table; and woody vegetation, which has decreased over time. Chapter Two inspects the oft-asserted claim that escaped fires from oil palm concessions and smallholder farms near settlements are the primary sources of fire ignitions. We evaluate fire origin and spread, and find that most fires originate in non-forest, compared to oil palm concessions, and relatively few originate close to settlements. Moreover, most fires started within oil palm concessions and in close proximity to settlements stay within those boundaries. However, fire ignition density in oil palm concessions and close to settlements is high. Furthermore, increased anthropogenic activity in close proximity to oil palm concessions and settlements produces a detectable pattern of fire activity. These results refute the claim that most fires originate in oil palm concessions, and that fires escaping from oil palm concessions and settlements constitute a major proportion of fires in this study region. However, there is a potential for these land use types to contribute more substantially to the fire landscape if their area expands. Chapter Three examines the potential for the financial incentive mechanism of Roundtable on Sustainable Palm Oil (RSPO) certification, which prohibits the use of fire on certified concessions, to reduce fire activity on oil palm concessions. We examine if RSPO-certified concessions have reduced fire activity in Sumatra and Kalimantan, the leading producers of oil palm both within Indonesia and globally. We also evaluate if this pattern changes with increasing likelihood of fires. These questions are particularly critical in fuel-rich peatland areas, of which approximately 46% was designated as oil palm concession as of 2010. We find that fire activity is significantly lower on RSPO certified concessions than non-RSPO certified concessions when the likelihood of fire is low (i.e., on non-peatlands in wetter years), but not when the likelihood of fire is high (i.e., on non-peatlands in dry years or on peatlands). These chapters advance our understanding of how anthropogenic factors influence the controls of fire in Kalimantan and Sumatra, both directly (i.e., human-caused ignitions) and indirectly (i.e., changing the susceptibility of the landscape to ignitions and to burning). The findings presented in this dissertation indicate that oil palm concessions are associated with high fire probability (Chapter One) and a substantial amount of ignitions and relatively high ignition density (Chapter Two). One of the more pointed ways to target fire on oil palm concessions is through RSPO certification; however, we find that certification is only effective when fire likelihood is already low, suggesting that, in order for this mechanism to reduce fire, more assistance may be needed to control fires in dry years and on peatlands (Chapter Three). Non-forested, degraded areas contribute much more to fire activity than oil palm on this landscape; these areas experience the greatest number of ignitions, have highest ignition density, and are the primary source of forest fires (Chapter Two). Furthermore, the declines in vegetation and the hydrological alteration in these degraded areas contribute substantially to fire occurrence (Chapter One). Effective fire management in this area, including fire prevention and suppression efforts, should therefore target not just oil palm concessions and smallholdings around settlements, but should also focus strongly on non-forested, degraded areas – and in particular those near oil palm concession boundaries and outside the immediate vicinity of settlements – where fire probability is high and where ignitions and fires escaping into forest are most likely to occur. Rehabilitation of the degraded landscape through restoring hydrology and replanting will be key to fire reduction, and can offset the effects of climate on fire in this landscape. The methodological approaches in this dissertation demonstrate ways in which remote sensing and analytical technologies can be used to answer complex questions about coupled human and natural systems that fuse social and environmental data, for both theoretical and management applications. Chapter One uses biophysical information from remotely sensed products and fieldwork with information about human access on the landscape and integrates them together with Moderate Resolution Imaging Spectroradiometer (MODIS) Active Fire detections under a Bayesian framework. Chapters Two and Three use a novel technique to cluster remotely sensed data on fire occurrence (MODIS Active Fire detections) into fire events so that ignitions can be isolated. This technique allows us to answer questions related to fire origin, spread, and impact that cannot be investigated by evaluating fire detections alone. This dissertation addresses a gap in knowledge regarding the anthropogenic contributions to increased fire probability and to ignitions in peat swamp, and the approaches could be applied to other degraded peatland areas in Indonesia that are candidate sites for restoration (e.g., under the newly established Peatland Restoration Agency), and to degraded peatlands that experience a novel fire regime in other parts of the tropics. Furthermore, this dissertation evaluates the capacity for RSPO certification to reduce fire activity on oil palm concessions across Sumatra and Kalimantan, Indonesia, and the analyses conducted could be applied to landscapes in other parts of the tropics experiencing oil palm development. In conclusion, the research findings presented in this dissertation are a product of combining social and environmental data and evaluating this data with a suite of classic and novel modeling approaches. This dissertation is presented in the hope that it contributes to our understanding of fire dynamics in the globally important peat-swamp forest, Indonesia, and thus our capacity to manage these disturbances

Effectiveness of Roundtable on Sustainable Palm Oil (RSPO) for reducing fires on oil palm concessions in Indonesia from 2012 to 2015

Fire is a common tool for land conversion and management associated with oil palm production. Fires can cause biodiversity and carbon losses, emit pollutants that deteriorate air quality and harm human health, and damage property. The Roundtable on Sustainable Palm Oil (RSPO) prohibits the use of fire on certified concessions. However, efforts to suppress fires are more difficult during El Niño conditions and on peatlands. In this paper, we address the following questions for oil palm concessions developed prior to 2012 in Sumatra and Kalimantan, the leading producers of oil palm both within Indonesia and globally: (1) for the period 2012–2015, did RSPO-certified concessions have a lower density of fire detections, fire ignitions, or 'escaped' fires compared with those concessions that are not certified? and (2) did this pattern change with increasing likelihood of fires in concessions located on peatland and in dry years? These questions are particularly critical in fuel-rich peatlands, of which approximately 46% of the area was designated as oil palm concession as of 2010. We conducted propensity scoring to balance covariate distributions between certified and non-certified concessions, and we compare the density of fires in certified and non-certified concessions using Kolmogorov–Smirnov tests based on moderate resolution imaging spectroradiometer Active Fire Detections from 2012–2015 clustered into unique fire events. We find that fire activity is significantly lower on RSPO certified concessions than non-RSPO certified concessions when the likelihood of fire is low (i.e., on non-peatlands in wetter years), but not when the likelihood of fire is high (i.e., on non-peatlands in dry years or on peatlands). Our results provide evidence that RSPO has the potential to reduce fires, though it is currently only effective when fire likelihood is relatively low. These results imply that, in order for this mechanism to reduce fire, additional strategies will be needed to control fires in oil palm plantations in dry years and on peatlands

Forecasting Natural Regeneration of Sagebrush After Wildfires Using Population Models and Spatial Matching

Context Addressing ecosystem degradation in the Anthropocene will require ecological restoration across large spatial extents. Identifying areas where natural regeneration will occur without direct resource investment will improve scalability of restoration actions. Objectives An ecoregion in need of large scale restoration is the Great Basin of the Western US, where increasingly large and frequent wildfires threaten ecosystem integrity and its foundational shrub species. We develop a framework to forecast where postwildfire regeneration of sagebrush cover (Artemisia spp.) is likely to occur within the burnt areas across the region (\u3e900,000 km2). Methods First, we parameterized population models using Landsat satellite-derived time series of sagebrush cover. Second, we evaluated the out-of-sample performance by predicting natural regeneration in wildfres not used for model training. This model assessment reproduces a management-oriented scenario: making restoration decisions shortly after wildfires with minimal local information. Third, we asked how accounting for increasingly fine-scale spatial heterogeneity could improve model forecasting accuracy. Results Regional-level models revealed that sagebrush post-fire recovery is slow, estimating \u3e 80-year time horizon to reach an average cover at equilibrium of 16.6% (CI95% 9–25). Accounting for wildfre and within-wildfre spatial heterogeneity improved out-ofsample forecasts, resulting in a mean absolute error of 3.5 ± 4.3% cover, compared to the regional model with an error of 7.2 ± 5.1% cover. Conclusions We demonstrate that combining population models and non-parametric spatial matching provides a fexible framework for forecasting plant population recovery. Models for population recovery applied to Landsat-derived time series will assist restoration decision-making, including identifying priority targets for restoration

Declining severe fire activity on managed lands in Equatorial Asia

Abstract: Fire activity is declining globally due to intensifying land management, but trends remain uncertain for the humid tropics, particularly Equatorial Asia. Here, we report that rates of fire events deemed severe (≥75th severity percentile of 2002-2019) and very severe (≥90th percentile) for Indonesia declined 19-27% and 23-34% over 2002-2019, respectively, controlling for precipitation, where fire-event severity is given by total fire radiative power and duration. The severity of seasonal fire activity – a measure of extremeness – declined 16% in Sumatra and moderately elsewhere. Declines concentrated over mosaic croplands and nearby forest, accounting for one-fifth and one-quarter of fire activity, respectively, with each class contracting 11% amongst severe fire events. Declines were limited over mosaic lands with relatively limited cropping, despite accounting for a similar extent and one-fifth share of fire activity. Declines had an uncertain association with agricultural development but seemingly reflect related political and economic forces for economic and environmental security

Cyberinfrastructure Deployments on Public Research Clouds Enable Accessible Environmental Data Science Education

Modern science depends on computers, but not all scientists have access to the scale of computation they need. A digital divide separates scientists who accelerate their science using large cyberinfrastructure from those who do not, or who do not have access to the compute resources or learning opportunities to develop the skills needed. The exclusionary nature of the digital divide threatens equity and the future of innovation by leaving people out of the scientific process while over-amplifying the voices of a small group who have resources. However, there are potential solutions: recent advancements in public research cyberinfrastructure and resources developed during the open science revolution are providing tools that can help bridge this divide. These tools can enable access to fast and powerful computation with modest internet connections and personal computers. Here we contribute another resource for narrowing the digital divide: scalable virtual machines running on public cloud infrastructure. We describe the tools, infrastructure, and methods that enabled successful deployment of a reproducible and scalable cyberinfrastructure architecture for a collaborative data synthesis working group in February 2023. This platform enabled 45 scientists with varying data and compute skills to leverage 40,000 hours of compute time over a 4-day workshop. Our approach provides an open framework that can be replicated for educational and collaborative data synthesis experiences in any data- and compute-intensive discipline

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on \u3e100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

Fire as a fundamental ecological process: Research advances and frontiers

© 2020 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire-dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above-ground ecology, (d) fire effects on below-ground ecology, (e) fire behaviour and (f) fire ecology modelling. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. Synthesis: As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Non peer reviewe