globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2832
论文题名:
Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests
作者: Ryan Kelly
刊名: Nature Climate Change
ISSN: 1758-732X
EISSN: 1758-6852
出版年: 2015-10-19
卷: Volume:6, 页码:Pages:79;82 (2016)
语种: 英语
英文关键词: Ecosystem ecology ; Climate-change ecology ; Palaeoecology ; Biogeochemistry
英文摘要:

Wildfires play a key role in the boreal forest carbon cycle1, 2, and models suggest that accelerated burning will increase boreal C emissions in the coming century3. However, these predictions may be compromised because brief observational records provide limited constraints to model initial conditions4. We confronted this limitation by using palaeoenvironmental data to drive simulations of long-term C dynamics in the Alaskan boreal forest. Results show that fire was the dominant control on C cycling over the past millennium, with changes in fire frequency accounting for 84% of C stock variability. A recent rise in fire frequency inferred from the palaeorecord5 led to simulated C losses of 1.4kgCm−2 (12% of ecosystem C stocks) from 1950 to 2006. In stark contrast, a small net C sink of 0.3kgCm−2 occurred if the past fire regime was assumed to be similar to the modern regime, as is common in models of C dynamics. Although boreal fire regimes are heterogeneous, recent trends6 and future projections7 point to increasing fire activity in response to climate warming throughout the biome. Thus, predictions8 that terrestrial C sinks of northern high latitudes will mitigate rising atmospheric CO2 may be over-optimistic.

The Arctic has experienced rapid climate change in recent decades and is projected to warm 4–5°C—more than twice the global average—during the twenty-first century under moderate anthropogenic emissions scenarios9. High-latitude ecosystems impose critical feedbacks to global climate change by modulating the rise in atmospheric concentration of greenhouse gases. In particular, the vast boreal forest biome is estimated to serve as a net C sink of ~0.5PgCyr−1 (ref. 10), contributing substantially to a global terrestrial sink of 1–1.5PgCyr−1 in recent decades9. Longer growing seasons and rising atmospheric CO2 concentration (pCO2) could enhance boreal forest productivity in the twenty-first century, and Earth system models (ESMs) indicate that these effects will strengthen the boreal C sink8. However, observed recent trends have been heterogeneous11, and the sustainability of continued C uptake by the biome depends on many interacting factors that remain poorly understood, including changing disturbance regimes, thawing permafrost, and nutrient limitation. To constrain models of the global C cycle, it is critical to understand how these processes operate within boreal ecosystems and to scale their behaviour to the entire biome.

Wildfire plays a dominant role in the C dynamics of boreal forests2, 3. In recent decades, climate warming has been linked to increased boreal forest burning, including record-breaking fire years and unprecedented regional fire regimes5, 6, 7, and future climate change is expected to increase fire activity throughout the biome7. The potential for these changes to feed back to the climate system has not been formally evaluated using ESMs, because the inclusion of fire in such models is a relatively new development8, 12. However, ecosystem models suggest that C emissions resulting from even moderate increases in burning could offset enhanced productivity caused by CO2 fertilization and climate change13, potentially converting the boreal biome from a sink to a source of C within the next century3, 14.

Efforts to model fire effects on boreal C cycling may be compromised by the brevity of observational fire records, which span only the past several decades in most boreal regions. The ‘spin-up procedure commonly used to initialize ecosystem models often requires hundreds to thousands of model years to reach an approximately steady state, and, for lack of empirical data, prehistoric fire regimes are typically assumed to be stationary and similar to modern for the purpose of the spin-up. Model results depend strongly on this assumption3, 4, 15, and recent palaeoecological studies have challenged it by revealing striking variability in past boreal forest fire activity16, 17. In particular, a fire history reconstruction from the Yukon Flats ecoregion of Alaska indicates transition to a new fire regime within the past several decades, providing unambiguous evidence that the modern fire regime is unrepresentative of prehistoric variability5. The Yukon Flats region has experienced among the most extensive burning of any North American boreal forest in recent years18, and may therefore be indicative of widespread future change if predictions of increased burning are realized. Here we use palaeoecological data from this region as a basis for ecosystem modelling experiments to elucidate the implications of past fire-regime change to present and future C balance.

We modelled C dynamics of the past millennium (850–2006) for ~2,000km2 of boreal forest in the Yukon Flats (Supplementary Fig. 1) using the dynamic organic soil version of the Terrestrial Ecosystem Model (DOS-TEM), a process-based model designed to simulate the cycling of carbon and nitrogen through the soil and vegetation of terrestrial ecosystems (Methods and Supplementary Fig. 2). We forced the model with fire frequency and severity proxies derived from sediment charcoal records5, palaeoclimate simulations generated by the Max Planck Institute for Meteorology Earth System Model (MPI-ESM; ref. 19), and ice-core pCO2 records20. Simulated total ecosystem carbon storage (CECO) was highly variable over centennial timescales (Figs 1 and 2a), ranging from 9.6kgCm−2 in 1230 to a maximum of 12.5kgCm−2 in 1870. Model experiments in which each forcing was allowed to vary or held stationary reveal that the majority (83.5%) of CECO variability was due to shifts in fire frequency, and most of the remainder (14.6% of total) was accounted for by fire severity. The direct effects of climate and pCO2 were minor (1.6% and <0.1% of CECO variance, respectively). Thus, long-term C dynamics of the past millennium were almost entirely dictated by patterns of fire-regime variability.

Figure 1: Carbon dynamics of the past millennium.
Carbon dynamics of the past millennium.

a, Simulated carbon stocks in response to model drivers (bf) applied in combination (black) or individually (colours; see legend). Results are plotted as deviations from a control simulation with stationary inputs. b, Fire frequency estimated from palaeorecords. c, Fire-severity class (thick line) derived by stratifying a proxy variable (thin line) at its upper and lower quartiles (grey lines). d,e, Simulated palaeoclimate, summarized as trends in annual temperature and precipitation (actual inputs were monthly and included additional variables). f, Atmospheric CO2 concentration from ice-core records. All lines are means over the study area.

Overview.

We used the dynamic organic soil version of the Terrestrial Ecosystem Model (DOS-TEM) to simulate C dynamics of the past millennium (the actual range of 850–2006 was chosen based on data availability), driven by forcings that included palaeofire reconstructions5, palaeoclimate simulations19 spliced with observational climate data28, and pCO2 values from modern observations combined with ice-core data20. We also conducted model experiments in which each of these inputs was held stationary or allowed to vary, to determine the contribution of each to overall variability in past C storage.

To evaluate the impact of typical spin-up assumptions on modelled C dynamics, we ran two DOS-TEM experiments spanning 1950–2006, the period for which reliable observational fire records exist18. Fire occurrence was prescribed directly from these observations, and climate and pCO2 forcings were derived from the observation-based portions of the data sets described above. The spModern experiment followed a typical spin-up procedure in which the model was initially driven by modern forcings, repeated continuously until dynamic equilibrium was achieved, which typically requires ~1,000 model years for boreal forest ecosystems owing to large C stocks and slow turnover of deep soil C pools. The resulting modelled ecosystem state then served as the starting point for the spModern experiment. By contrast, the spPaleo experiment began from the 1950 model state of our past-millennium simulation. Thus, differences between the spModern and spPaleo simulations can be attributed to the replacement of spin-up assumptions with estimates of past environmental variability informed by palaeodata.

Study area.

We ran DOS-TEM on a 1-km2 grid delineated by the union of circular buffers of 10-km radius around each of the 14 sampling sites contributing to our palaeofire records5 (Supplementary Fig. 1). This results in a contiguous area of 1,931km2, for which previous validation exercises confirmed that the charcoal data accurately capture observed patterns of recent burning. The area is near the southern boundary of the Yukon Flats ecoregion of interior Alaska. The region has a dry continental climate characterized by mean (1971–2000 climatology) January and July temperatures of −22.2 and 17.5°C, respectively, and mean annual precipitation of 24.9cm (ref. 28). Vegetation is primarily a matrix of black spruce (Picea mariana) and deciduous species (for example, Populus tremuloides) in various stages of postfire succession, as is typical of interior Alaska. Soils range from poorly to well drained, depending on landscape position29.

Model description.

DOS-TEM is a process-based model designed to simulate the cycling of carbon and nitrogen through the soil and vegetation of terrestrial ecosystems. The model is composed of four interacting modules (Supplementary Fig. 2): the environmental module uses climate information to calculate the dynamics of biophysical processes (for example, soil temperature and moisture); the ecological module uses information about vegetation composition, atmospheric and soil environment, and soil structure to calculate pools and fluxes of carbon and nitrogen; the dynamic organic soil module models loss and accumulation of soil organic matter due to fire and succession, and the thermal and hydrologic consequences of these changes; and the disturbance module calculates the fate of ecosystem carbon and nitrogen after fire, based on topography, climate conditions, soil characteristics, and fire severity.

DOS-TEM has been developed extensively for use in boreal forest ecosystems23, 30, 31, 32. In particular, the model produces realistic temporal patterns of postfire ecosystem recovery, which dominate long-term CECO variability in our model experiments. Although numerous factors (for example, site drainage, fire severity, climate) influence successional dynamics in DOS-TEM, simulated burned areas generally lose C for one to two decades following fire before transitioning to a C sink, with peak C gains occurring 30–70 years after the burn30, 32. These changes arise from mechanisms of vegetation recovery (via parametric formulations; DOS-TEM does not explicitly model vegetation community dynamics) and soil development that have been formally validated in the context of chronosequence and forest inventory data30, 31, 33, and they are consistent with a number of other empirical studies34, 35. The responses of the model to warming and rising pCO2 have also been evaluated in the context of boreal forest C dynamics, and are generally consistent with available data15. Indeed, the moderate C sink of recent decades simulated by our spModern experiment is consistent with other model-based estimates in the absence of long-term fire history information10.

Fire-frequency forcing data.

To prescribe fire occurrence in our past-millennium experiments, we used a palaeorecord of reconstructed fire frequency from the Yukon Flats ecoregion of Alaska (Fig. 1b). The record is a composite of individual fire events identified by analysing charcoal deposits in sediment cores from 14 lakes, and was previously shown to accurately represent the regional fire regime within an ~2,000-km2 area surrounding the lakes5. DOS-TEM requires fires to be prescribed annually for each simulated cell on the landscape, whereas the Yukon Flats palaeorecord represents regional variability on decadal–centennial timescales. To convert charcoal-inferred fire frequency to a DOS-TEM driver, in each simulated year we multiplied regional fire frequency by the number of simulated cells to determine the total number of burned cells to prescribe. The spatial arrangement of burned area is unimportant in DOS-TEM because grid cells do not interact, so we did not attempt to mimic real fire size distributions or connectivity of burned areas. Instead, we prescribed burned grid cell locations initially at random and, after all cells had burned at least once, we chose the specific cells to burn in each model year as those that had been longest without fire. This strategy reflects the observation that the flammability of boreal forest stands increases as fire-prone spruce species replace early successional deciduous species36. For past-millennium experiments requiring stationary fire frequency (that is, those designed to isolate the influence of one of the other forcing variables), we followed the procedure outlined above, but prescribed constant frequency equal to the past-millennium mean. For the spPaleo and spModern experiments, individual fires from 1950 to 2006 were prescribed from the database of observed fire perimeters in Alaska18. These observed fires were also used to derive a single estimate of modern fire frequency to specify spin-up fire occurrence for the spModern experiment, following the typical assumption when historic fire data are unavailable15.

Fire-severity forcing data.

DOS-TEM simulates fire severity as a categorical variable with three classes. For the past-millennium simulation we assigned fires to these classes based on a record of charcoal production per fire derived from the Yukon Flats palaeodata (Fig. 1c). Previous analysis identified this metric as a qualitative proxy for past fire severity in the region, although we acknowledge there is considerable uncertainty associated with this interpretation5. We separated the record into three levels using its lower and upper quartiles of the past millennium, and mapped these to the DOS-TEM severity classes (Fig. 1c). For each simulation year, we assigned the severity class thus determined to all fires in that year. In past-millennium experiments lacking fire-severity variability, we defined all fires as moderate severity. For the spModern and spPaleo experiments we prescribed fire severity for the period 1950–2006 following the default procedure in DOS-TEM, which is based on empirical relationships involving burn season, vegetation type, and site drainage32.

Climate forcing data.

DOS-TEM requires monthly inputs of mean temperature, total precipitation, vapour pressure, and incoming radiation (Fig. 1d, e). We obtained these data from a palaeoclimate simulation spanning 850–1950 using the Max Plank Institute Earth System Model (MPI-ESM; ref. 19). We merged the simulated palaeoclimate to observation-based climate data for 1900–2006 derived from observationsURL:

http://www.nature.com/nclimate/journal/v6/n1/full/nclimate2832.html
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/4560
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
nclimate2832.pdf(531KB)期刊论文作者接受稿开放获取View Download

Recommended Citation:
Ryan Kelly. Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests[J]. Nature Climate Change,2015-10-19,Volume:6:Pages:79;82 (2016).
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Ryan Kelly]'s Articles
百度学术
Similar articles in Baidu Scholar
[Ryan Kelly]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Ryan Kelly]‘s Articles
Related Copyright Policies
Null
收藏/分享
文件名: nclimate2832.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.