diff --git a/docs_src/sphinx/source/bibliography.bib b/docs_src/sphinx/source/bibliography.bib new file mode 100644 index 00000000..7c7dbc6c --- /dev/null +++ b/docs_src/sphinx/source/bibliography.bib @@ -0,0 +1,542 @@ +@article{balshi2007role, + title = {The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: A process-based analysis}, + author = {M. S. Balshi and A. D. McGuire and Q. Zhuang and J. Melillo and D. W. Kicklighter and E. Kasischke and C. Wirth and M. Flannigan and J. Harden and J. S. Clein and T. J. Burnside and J. McAllister and W. A. Kurz and M. Apps and A. Shvidenko}, + year = 2007, + month = 6, + journal = {Journal of Geophysical Research: Biogeosciences}, + publisher = {Blackwell Publishing Ltd}, + volume = 112, + doi = {10.1029/2006JG000380}, + issn = {01480227}, + abstract = {Wildfire is a common occurrence in ecosystems of northern high latitudes, and changes in the fire regime of this region have consequences for carbon feedbacks to the climate system. To improve our understanding of how wildfire influences carbon dynamics of this region, we used the process-based Terrestrial Ecosystem Model to simulate fire emissions and changes in carbon storage north of 45°N from the start of spatially explicit historically recorded fire records in the twentieth century through 2002, and evaluated the role of fire in the carbon dynamics of the region within the context of ecosystem responses to changes in atmospheric CO2 concentration and climate. Our analysis indicates that fire plays an important role in interannual and decadal scale variation of source/sink relationships of northern terrestrial ecosystems and also suggests that atmospheric CO2 may be important to consider in addition to changes in climate and fire disturbance. There are substantial uncertainties in the effects of fire on carbon storage in our simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. To improve the ability to better predict how fire will influence carbon storage of this region in the future, new analyses of the retrospective role of fire in the carbon dynamics of northern high latitudes should address these uncertainties. Copyright 2007 by the American Geophysical Union.}, + issue = 2 +} +@article{balshi2009assessing, + title = {Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach}, + author = {Michael S. Balshi and A. David McGuire and Paul Duffy and Mike Flannigan and John Walsh and Jerry Melillo}, + year = 2009, + journal = {Global Change Biology}, + volume = 15, + pages = {578--600}, + doi = {10.1111/J.1365-2486.2008.01679.X}, + issn = 13541013, + abstract = {Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5° (latitude × longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960-2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991-2000, the results suggest that average area burned per decade will double by 2041-2050 and will increase on the order of 3.5-5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long-term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics. © 2009 The Authors Journal compilation © 2009 Blackwell Publishing Ltd.}, + issue = 3, + keywords = {Boreal forest,Climate change,Fire,Future area burned,Multivariate Adaptive Regression Splines} +} +@article{balshi2009vulnerability, + title = {Vulnerability of carbon storage in North American boreal forests to wildfires during the 21st century}, + author = {Michael S. Balshi and A. D. Mcguire and P. Duffy and M. Flannigan and D. W. Kicklighter and J. Melillo}, + year = 2009, + journal = {Global Change Biology}, + volume = 15, + pages = {1491--1510}, + doi = {10.1111/J.1365-2486.2009.01877.X}, + issn = 13541013, + abstract = {The boreal forest contains large reserves of carbon. Across this region, wildfires influence the temporal and spatial dynamics of carbon storage. In this study, we estimate fire emissions and changes in carbon storage for boreal North America over the 21st century. We use a gridded data set developed with a multivariate adaptive regression spline approach to determine how area burned varies each year with changing climatic and fuel moisture conditions. We apply the process-based Terrestrial Ecosystem Model to evaluate the role of future fire on the carbon dynamics of boreal North America in the context of changing atmospheric carbon dioxide (CO2) concentration and climate in the A2 and B2 emissions scenarios of the CGCM2 global climate model. Relative to the last decade of the 20th century, decadal total carbon emissions from fire increase by 2.5-4.4 times by 2091-2100, depending on the climate scenario and assumptions about CO2 fertilization. Larger fire emissions occur with warmer climates or if CO2 fertilization is assumed to occur. Despite the increases in fire emissions, our simulations indicate that boreal North America will be a carbon sink over the 21st century if CO2 fertilization is assumed to occur in the future. In contrast, simulations excluding CO2 fertilization over the same period indicate that the region will change to a carbon source to the atmosphere, with the source being 2.1 times greater under the warmer A2 scenario than the B2 scenario. To improve estimates of wildfire on terrestrial carbon dynamics in boreal North America, future studies should incorporate the role of dynamic vegetation to represent more accurately post-fire successional processes, incorporate fire severity parameters that change in time and space, account for human influences through increased fire suppression, and integrate the role of other disturbances and their interactions with future fire regime. © 2009 Blackwell Publishing.}, + issue = 6, + keywords = {Boreal carbon dynamics,Climate change,Fire emissions} +} +@article{beringer2001representation, + title = {The Representation of Arctic Soils in the Land Surface Model: The Importance of Mosses}, + author = {Jason Beringer and Amanda H Lynch and F Stuart Chapin and Michelle Mack and Gordon B Bonan}, + year = 2001, + journal = {Journal of Climate}, + publisher = {American Meteorological Society}, + volume = 14, + pages = {3324--3335}, + doi = {10.1175/1520-0442(2001)014<3324:TROASI>2.0.CO;2}, + url = {https://journals.ametsoc.org/view/journals/clim/14/15/1520-0442_2001_014_3324_troasi_2.0.co_2.xml}, + city = {Boston MA, USA}, + issue = 15 +} +@article{briones2024exploring, + title = {Exploring the interplay between soil thermal and hydrological changes and their impact on carbon fluxes in permafrost ecosystems}, + author = {Valeria Briones and Elchin E Jafarov and Hélène Genet and Brendan M Rogers and Ruth M Rutter and Tobey B Carman and Joy Clein and Eugénie S Euschkirchen and Edward AG Schuur and Jennifer D Watts and Susan M Natali}, + year = 2024, + month = 7, + journal = {Environmental Research Letters}, + volume = 19, + pages = {074003}, + doi = {10.1088/1748-9326/ad50ed}, + issn = {1748-9326}, + abstract = {

Accelerated warming of the Arctic can affect the global climate system by thawing permafrost and exposing organic carbon in soils to decompose and release greenhouse gases into the atmosphere. We used a process-based biosphere model (DVM-DOS-TEM) designed to simulate biophysical and biogeochemical interactions between the soil, vegetation, and atmosphere. We varied soil and environmental parameters to assess the impact on cryohydrological and biogeochemical outputs in the model. We analyzed the responses of ecosystem carbon balances to permafrost thaw by running site-level simulations at two long-term tundra ecological monitoring sites in Alaska: Eight Mile Lake (EML) and Imnavait Creek Watershed (IMN), which are characterized by similar tussock tundra vegetation but differing soil drainage conditions and climate. Model outputs showed agreement with field observations at both sites for soil physical properties and ecosystem CO 2 fluxes. Model simulations of Net Ecosystem Exchange (NEE) showed an overestimation during the frozen season (higher CO 2 emissions) at EML with a mean NEE of 26.98 ± 4.83 gC/m 2 /month compared to observational mean of 22.01 ± 5.67 gC/m 2 /month, and during the fall months at IMN, with a modeled mean of 19.21 ± 7.49 gC/m 2 /month compared to observation mean of 11.9 ± 4.45 gC/m 2 /month. Our results underscore the importance of representing the impact of soil drainage conditions on the thawing of permafrost soils, particularly poorly drained soils, which will drive the magnitude of carbon released at sites across the high-latitude tundra. These findings can help improve predictions of net carbon releases from thawing permafrost, ultimately contributing to a better understanding of the impact of Arctic warming on the global climate system.

}, + issue = 7 +} + +@article{decker2009impact, + title = {Impact of Modified Richards Equation on Global Soil Moisture Simulation in the Community Land Model (CLM3.5)}, + author = {Mark Decker and Xubin Zeng}, + year = 2009, + month = 3, + journal = {Journal of Advances in Modeling Earth Systems}, + publisher = {American Geophysical Union (AGU)}, + volume = 1, + doi = {10.3894/JAMES.2009.1.5}, + issn = {1942-2466}, + abstract = {A fundamental deficiency has been found in the numerical solution of the soil moisture‐based Richards equation using the mass‐conservative scheme in the Community Land Model (CLM) in the first part of our efforts ( Zeng and Decker 2009). This study implements the revised form of the Richards equation from that study (which doesn't change the property of the differential equation but does remove the deficiency of the numerical solution) along with a new bottom boundary condition into the current version of CLM (CLM3.5) for global offline modeling evaluations. CLM3.5 represents a significant improvement over its earlier version (CLM3.0), but it also introduces a new deficiency in the vertical distribution of the soil moisture variability. Mean soil moisture in CLM3.5 is also too wet. It is found that the new treatments (primarily a numerically correct solution of Richards equation with a new bottom boundary condition) with minimal tuning are able to maintain the improvements of the CLM3.5 over CLM3.0 and, at the same time, remove the new deficiencies of CLM3.5 based on in situ and satellite data analysis. Because the deficiency in the numerical solution of the soil moisture‐based Richards equation is also expected in other land models, implementation details are provided to facilitate similar tests using other land models in the future.}, + issue = 3 +} +@misc{eaton2011netcdf, + title = {NetCDF Climate and Forecast (CF) Metadata Conventions}, + author = {B. Eaton and J. Gregory and B. Drach and K. Taylor and S. Hankin and J. Caron and R. Signell and P. Bentley and G. Rappa and H. Höck and A. Pamment and M. Juckes}, + year = 2011, + url = {https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html} +} +@article{euskirchen2006importance, + title = {Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems}, + author = {E. S. Euskirchen and A. D. McGuire and D. W. Kicklighter and Q. Zhuang and J. S. Clein and R. J. Dargaville and D. G. Dye and J. S. Kimball and K. C. McDonald and J. M. Melillo and V. E. Romanovsky and N. V. Smith}, + year = 2006, + month = 4, + journal = {Global Change Biology}, + volume = 12, + pages = {731--750}, + doi = {10.1111/J.1365-2486.2006.01113.X}, + issn = 13541013, + abstract = {In terrestrial high-latitude regions, observations indicate recent changes in snow cover, permafrost, and soil freeze-thaw transitions due to climate change. These modifications may result in temporal shifts in the growing season and the associated rates of terrestrial productivity. Changes in productivity will influence the ability of these ecosystems to sequester atmospheric CO2. We use the terrestrial ecosystem model (TEM), which simulates the soil thermal regime, in addition to terrestrial carbon (C), nitrogen and water dynamics, to explore these issues over the years 1960-2100 in extratropical regions (30-90°N). Our model simulations show decreases in snow cover and permafrost stability from 1960 to 2100. Decreases in snow cover agree well with National Oceanic and Atmospheric Administration satellite observations collected between the years 1972 and 2000, with Pearson rank correlation coefficients between 0.58 and 0.65. Model analyses also indicate a trend towards an earlier thaw date of frozen soils and the onset of the growing season in the spring by approximately 2-4 days from 1988 to 2000. Between 1988 and 2000, satellite records yield a slightly stronger trend in thaw and the onset of the growing season, averaging between 5 and 8 days earlier. In both, the TEM simulations and satellite records, trends in day of freeze in the autumn are weaker, such that overall increases in growing season length are due primarily to earlier thaw. Although regions with the longest snow cover duration displayed the greatest increase in growing season length, these regions maintained smaller increases in productivity and heterotrophic respiration than those regions with shorter duration of snow cover and less of an increase in growing season length. Concurrent with increases in growing season length, we found a reduction in soil C and increases in vegetation C, with greatest losses of soil C occurring in those areas with more vegetation, but simulations also suggest that this trend could reverse in the future. Our results reveal noteworthy changes in snow, permafrost, growing season length, productivity, and net C uptake, indicating that prediction of terrestrial C dynamics from one decade to the next will require that large-scale models adequately take into account the corresponding changes in soil thermal regimes. © 2006 Blackwell Publishing Ltd.}, + issue = 4, + keywords = {Carbon sequestration,Climate change,Growing season,Permafrost,Productivity,Respiration,Snow cover,Terrestrial ecosystem model} +} +@article{euskirchen2009changes, + title = {Changes in vegetation in northern Alaska under scenarios of climate change, 2003-2100: implications for climate feedbacks}, + author = {E. S. Euskirchen and A. D. Mcguire and F. S. Chapin and S. Yi and C. C. Thompson}, + year = 2009, + month = 7, + journal = {Ecological Applications}, + volume = 19, + pages = {1022--1043}, + doi = {10.1890/08-0806.1}, + issn = 10510761, + abstract = {Assessing potential future changes in arctic and boreal plant species productivity, ecosystem composition, and canopy complexity is essential for understanding environmental responses under expected altered climate forcing. We examined potential changes in the dominant plant functional types (PFTs) of the sedge tundra, shrub tundra, and boreal forest ecosystems in ecotonal northern Alaska, USA, for the years 2003-2100. We compared energy feedbacks associated with increases in biomass to energy feedbacks associated with changes in the duration of the snow-free season. We based our simulations on nine input climate scenarios from the Intergovernmental Panel on Climate Change (IPCC) and a new version of the Terrestrial Ecosystem Model (TEM) that incorporates biogeochemistry, vegetation dynamics for multiple PFTs (e.g., trees, shrubs, grasses, sedges, mosses), multiple vegetation pools, and soil thermal regimes. We found mean increases in net primary productivity (NPP) in all PFTs. Most notably, birch (Betula spp.) in the shrub tundra showed increases that were at least three times larger than any other PFT. Increases in NPP were positively related to increases in growing-season length in the sedge tundra, but PFTs in boreal forest and shrub tundra showed a significant response to changes in light availability as well as growing-season length. Significant NPP responses to changes in vegetation uptake of nitrogen by PFT indicated that some PFTs were better competitors for nitrogen than other PFTs. While NPP increased, heterotrophic respiration (RH) also increased, resulting in decreases or no change in net ecosystem carbon uptake. Greater aboveground biomass from increased NPP produced a decrease in summer albedo, greater regional heat absorption (0.34 6 0.23 W·m-1·10 yr-1 [mean ±; SD]), and a positive feedback to climate warming. However, the decrease in albedo due to a shorter snow season (-5.1 ± 1.6 d/10 yr) resulted in much greater regional heat absorption (3.3 ±; 1.24 W·m-1·10 yr-1) than that associated with increases in vegetation. Through quantifying feedbacks associated with changes in vegetation and those associated with changes in the snow season length, we can reach a more integrated understanding of the manner in which climate change may impact interactions between highlatitude ecosystems and the climate system. © 2009 by the Ecological Society of America.}, + issue = 4, + keywords = {Arctic,Biogeochemistry model,Boreal,Climate feedbacks,Dynamic vegetation model,Future climate,Plant functional type,Soil thermal model,Terrestrial ecosystems}, + pmid = 19544741 +} +@article{euskirchen2014changes, + title = {Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf-out times across groupings of species in a dynamic vegetation model}, + author = {Eugénie S. Euskirchen and Tobey B. Carman and A. David Mcguire}, + year = 2014, + month = 3, + journal = {Global Change Biology}, + volume = 20, + pages = {963--978}, + doi = {10.1111/GCB.12392}, + issn = 13541013, + abstract = {The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970-2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf-out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf-out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions. © 2013 John Wiley & Sons Ltd.}, + issue = 3, + keywords = {Arctic tundra,Carbon cycling,Dynamic vegetation model,Ecosystem composition,Ecotonal boreal forest,Leaf phenology}, + pmid = 24105949 +} +@article{euskirchen2014differential, + title = {Differential response of carbon fluxes to climate in three peatland ecosystems that vary in the presence and stability of permafrost}, + author = {E. S. Euskirchen and C. W. Edgar and M. R. Turetsky and M. P. Waldrop and J. W. Harden}, + year = 2014, + month = 8, + journal = {Journal of Geophysical Research: Biogeosciences}, + volume = 119, + pages = {1576--1595}, + doi = {10.1002/2014JG002683}, + issn = 21698961, + abstract = {Changes in vegetation and soil properties following permafrost degradation and thermokarst development in peatlands may cause changes in net carbon storage. To better understand these dynamics, we established three sites in Alaska that vary in permafrost regime, including a black spruce peat plateau forest with stable permafrost, an internal collapse scar bog formed as a result of thermokarst, and a rich fen without permafrost. Measurements include year-round eddy covariance estimates of carbon dioxide (CO2), water, and energy fluxes, associated environmental variables, and methane (CH4) fluxes at the collapse scar bog. The ecosystems all acted as net sinks of CO2 in 2011 and 2012, when air temperature and precipitation remained near long-term means. In 2013, under a late snowmelt and late leaf out followed by a hot, dry summer, the permafrost forest and collapse scar bog were sources of CO2. In this same year, CO2 uptake in the fen increased, largely because summer inundation from groundwater inputs suppressed ecosystem respiration. CO2 exchange in the permafrost forest and collapse scar bog was sensitive to warm air temperatures, with 0.5 g C m-2 lost each day when maximum air temperature was very warm (≥29°C). The bog lost 4981 ± 300 mg CH4 m-2 between April and September 2013, indicating that this ecosystem acted as a significant source of both CO2 and CH4 to the atmosphere in 2013. These results suggest that boreal peatland responses to warming and drying, both of which are expected to occur in a changing climate, will depend on permafrost regime.}, + issue = 8 +} +@article{euskirchen2022assessing, + title = {Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities}, + author = {Eugénie S. Euskirchen and Shawn P. Serbin and Tobey B. Carman and Jennifer M. Fraterrigo and Hélène Genet and Colleen M. Iversen and Verity Salmon and A. David McGuire}, + year = 2022, + month = 3, + journal = {Ecological Applications}, + publisher = {Ecological Society of America}, + volume = 32, + doi = {10.1002/EAP.2499}, + issn = 19395582, + abstract = {As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.}, + issue = 2, + keywords = {arctic carbon budget,arctic tundra,landscape heterogeneity,model uncertainty,parameter sensitivity,terrestrial biosphere model}, + pmid = 34787932 +} +@article{fan2013response, + title = {The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change}, + author = {Zhaosheng Fan and Anthony David Mcguire and Merritt R. Turetsky and Jennifer W. Harden and James Michael Waddington and Evan S. Kane}, + year = 2013, + month = 2, + journal = {Global Change Biology}, + volume = 19, + pages = {604--620}, + doi = {10.1111/GCB.12041}, + issn = 13541013, + abstract = {It is important to understand the fate of carbon in boreal peatland soils in response to climate change because a substantial change in release of this carbon as CO2 and CH4 could influence the climate system. The goal of this research was to synthesize the results of a field water table manipulation experiment conducted in a boreal rich fen into a process-based model to understand how soil organic carbon (SOC) of the rich fen might respond to projected climate change. This model, the peatland version of the dynamic organic soil Terrestrial Ecosystem Model (peatland DOS-TEM), was calibrated with data collected during 2005-2011 from the control treatment of a boreal rich fen in the Alaska Peatland Experiment (APEX). The performance of the model was validated with the experimental data measured from the raised and lowered water-table treatments of APEX during the same period. The model was then applied to simulate future SOC dynamics of the rich fen control site under various CO2 emission scenarios. The results across these emissions scenarios suggest that the rate of SOC sequestration in the rich fen will increase between year 2012 and 2061 because the effects of warming increase heterotrophic respiration less than they increase carbon inputs via production. However, after 2061, the rate of SOC sequestration will be weakened and, as a result, the rich fen will likely become a carbon source to the atmosphere between 2062 and 2099. During this period, the effects of projected warming increase respiration so that it is greater than carbon inputs via production. Although changes in precipitation alone had relatively little effect on the dynamics of SOC, changes in precipitation did interact with warming to influence SOC dynamics for some climate scenarios.copy; 2012 Blackwell Publishing Ltd.}, + issue = 2, + keywords = {Boreal,Carbon,Climate change,Fen,Methane,Model,Peatland,Soil CO2 flux}, + pmid = 23504796 +} +@article{genet2013modeling, + title = {Modeling the effects of fire severity and climate warming on active layer thickness and soil carbon storage of black spruce forests across the landscape in interior Alaska}, + author = {H. Genet and A. D. McGuire and K. Barrett and A. Breen and E. S. Euskirchen and J. F. Johnstone and E. S. Kasischke and A. M. Melvin and A. Bennett and M. C. Mack and T. S. Rupp and A. E.G. Schuur and M. R. Turetsky and F. Yuan}, + year = 2013, + journal = {Environmental Research Letters}, + publisher = {Institute of Physics Publishing}, + volume = 8, + doi = {10.1088/1748-9326/8/4/045016}, + issn = 17489326, + abstract = {There is a substantial amount of carbon stored in the permafrost soils of boreal forest ecosystems, where it is currently protected from decomposition. The surface organic horizons insulate the deeper soil from variations in atmospheric temperature. The removal of these insulating horizons through consumption by fire increases the vulnerability of permafrost to thaw, and the carbon stored in permafrost to decomposition. In this study we ask how warming and fire regime may influence spatial and temporal changes in active layer and carbon dynamics across a boreal forest landscape in interior Alaska. To address this question, we (1) developed and tested a predictive model of the effect of fire severity on soil organic horizons that depends on landscape-level conditions and (2) used this model to evaluate the long-term consequences of warming and changes in fire regime on active layer and soil carbon dynamics of black spruce forests across interior Alaska. The predictive model of fire severity, designed from the analysis of field observations, reproduces the effect of local topography (landform category, the slope angle and aspect and flow accumulation), weather conditions (drought index, soil moisture) and fire characteristics (day of year and size of the fire) on the reduction of the organic layer caused by fire. The integration of the fire severity model into an ecosystem process-based model allowed us to document the relative importance and interactions among local topography, fire regime and climate warming on active layer and soil carbon dynamics. Lowlands were more resistant to severe fires and climate warming, showing smaller increases in active layer thickness and soil carbon loss compared to drier flat uplands and slopes. In simulations that included the effects of both warming and fire at the regional scale, fire was primarily responsible for a reduction in organic layer thickness of 0.06 m on average by 2100 that led to an increase in active layer thickness of 1.1 m on average by 2100. The combination of warming and fire led to a simulated cumulative loss of 9.6 kgC m-2 on average by 2100. Our analysis suggests that ecosystem carbon storage in boreal forests in interior Alaska is particularly vulnerable, primarily due to the combustion of organic layer thickness in fire and the related increase in active layer thickness that exposes previously protected permafrost soil carbon to decomposition. © 2013 IOP Publishing Ltd.}, + issue = 4, + keywords = {boreal forest,ecosystem model,fire severity,organic layer,permafrost,soil carbon} +} +@article{genet2018role, + title = {The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska:}, + author = {Hélène Genet and Yujie He and Zhou Lyu and A. David McGuire and Qianlai Zhuang and Joy Clein and David D'Amore and Alec Bennett and Amy Breen and Frances Biles and Eugénie S. Euskirchen and Kristofer Johnson and Tom Kurkowski and Svetlana Kushch Schroder and Neal Pastick and T. Scott Rupp and Bruce Wylie and Yujin Zhang and Xiaoping Zhou and Zhiliang Zhu}, + year = 2018, + month = 1, + journal = {Ecological Applications}, + publisher = {Ecological Society of America}, + volume = 28, + pages = {5--27}, + doi = {10.1002/EAP.1641}, + issn = 19395582, + abstract = {It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km2), are influencing and will influence state-wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO2), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950-2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (-6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010-2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO2, we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO2 increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.}, + issue = 1, + keywords = {Alaska carbon cycle,atmospheric CO2,carbon balance,climate change,fire,logging,permafrost,soil carbon,upland ecosystem,vegetation productivity}, + pmid = 29044791 +} +@article{hayes2011anorthern, + title = {Is the northern high-latitude land-based CO 2 sink weakening?}, + author = {D. J. Hayes and A. D. McGuire and D. W. Kicklighter and K. R. Gurney and T. J. Burnside and J. M. Melillo}, + year = 2011, + journal = {Global Biogeochemical Cycles}, + volume = 25, + doi = {10.1029/2010GB003813}, + issn = {08866236}, + abstract = {Studies indicate that, historically, terrestrial ecosystems of the northern high-latitude region may have been responsible for up to 60% of the global net land-based sink for atmospheric CO 2. However, these regions have recently experienced remarkable modification of the major driving forces of the carbon cycle, including surface air temperature warming that is significantly greater than the global average and associated increases in the frequency and severity of disturbances. Whether Arctic tundra and boreal forest ecosystems will continue to sequester atmospheric CO 2 in the face of these dramatic changes is unknown. Here we show the results of model simulations that estimate a 41 Tg C yr -1 sink in the boreal land regions from 1997 to 2006, which represents a 73% reduction in the strength of the sink estimated for previous decades in the late 20th century. Our results suggest that CO 2 uptake by the region in previous decades may not be as strong as previously estimated. The recent decline in sink strength is the combined result of (1) weakening sinks due to warming-induced increases in soil organic matter decomposition and (2) strengthening sources from pyrogenic CO 2 emissions as a result of the substantial area of boreal forest burned in wildfires across the region in recent years. Such changes create positive feedbacks to the climate system that accelerate global warming, putting further pressure on emission reductions to achieve atmospheric stabilization targets. Copyright 2011 by the American Geophysical Union.}, + issue = 3 +} +@article{hayes2011effects, + title = {The effects of land cover and land use change on the contemporary carbon balance of the arctic and boreal terrestrial ecosystems of Northern Eurasia}, + author = {Daniel J. Hayes and A. David McGuire and David W. Kicklighter and Todd J. Burnside and Jerry M. Melillo}, + year = 2011, + journal = {Eurasian Arctic Land Cover and Land Use in a Changing Climate}, + publisher = {Springer Netherlands}, + pages = {109--136}, + doi = {10.1007/978-90-481-9118-5_6}, + isbn = 9789048191178, + abstract = {Recent changes in climate, disturbance regimes and land use and management systems in Northern Eurasia have the potential to disrupt the terrestrial sink of atmospheric CO2 in a way that accelerates global climate change. To determine the recent trends in the carbon balance of the arctic and boreal ecosystems of this region, we performed a retrospective analysis of terrestrial carbon dynamics across northern Eurasia over a recent 10-year period using a terrestrial biogeochemical process model. The results of the simulations suggest a shift in direction of the net flux from the terrestrial sink of earlier decades to a net source on the order of 45 Tg C year-1 between 1997 and 2006. The simulation framework and subsequent analyses presented in this study attribute this shift to a large loss of carbon from boreal forest ecosystems, which experienced a trend of decreasing precipitation and a large area burned during this time period. © 2011 Springer Science+Business Media B.V.} +} +@article{jafarovINPREP2024, + title = {Estimation of above- and below-ground ecosystem parameters for the DVM-DOS-TEM model using MADS: a synthetic case study}, + author = {Elchin E. Jafarov and Hélène Genet Genet and Velimir V. (Monty) Vesselinov and Valeria Briones and Aiza Kabeer and Andrew L. Mullen and Benjamin Maglio and Tobey Carman and Ruth Rutter and Joy Clein and Chu-Chun Chang and Dogukan Teber and Trevor Smith and Joshua Rady and Christina Schädel and Jennifer D. Watts and Brendan M. Rogers and Susan Natali}, + journal = {Manuscript submitted for publication}, + year = 2024, +} +@article{jafarov2013effects, + title = {The effects of fire on the thermal stability of permafrost in lowland and upland black spruce forests of interior Alaska in a changing climate}, + author = {E. E. Jafarov and V. E. Romanovsky and H. Genet and A. D. McGuire and S. S. Marchenko}, + year = 2013, + journal = {Environmental Research Letters}, + volume = 8, + doi = {10.1088/1748-9326/8/3/035030}, + issn = 17489326, + abstract = {Fire is an important factor controlling the composition and thickness of the organic layer in the black spruce forest ecosystems of interior Alaska. Fire that burns the organic layer can trigger dramatic changes in the underlying permafrost, leading to accelerated ground thawing within a relatively short time. In this study, we addressed the following questions. (1) Which factors determine post-fire ground temperature dynamics in lowland and upland black spruce forests? (2) What levels of burn severity will cause irreversible permafrost degradation in these ecosystems? We evaluated these questions in a transient modeling-sensitivity analysis framework to assess the sensitivity of permafrost to climate, burn severity, soil organic layer thickness, and soil moisture content in lowland (with thick organic layers, ∼80 cm) and upland (with thin organic layers, ∼30 cm) black spruce ecosystems. The results indicate that climate warming accompanied by fire disturbance could significantly accelerate permafrost degradation. In upland black spruce forest, permafrost could completely degrade in an 18 m soil column within 120 years of a severe fire in an unchanging climate. In contrast, in a lowland black spruce forest, permafrost is more resilient to disturbance and can persist under a combination of moderate burn severity and climate warming. © 2013 IOP Publishing Ltd.}, + issue = 3 +} +@article{johnstone2010changes, + title = {Changes in fire regime break the legacy lock on successional trajectories in Alaskan boreal forest}, + author = {Jill F. Johnstone and Teresa N. Hollingsworth and F. Stuart Chapin and Michelle C. Mack}, + year = 2010, + journal = {Global Change Biology}, + volume = 16, + doi = {10.1111/j.1365-2486.2009.02051.x}, + issn = 13541013, + abstract = {Predicting plant community responses to changing environmental conditions is a key element of forecasting and mitigating the effects of global change. Disturbance can play an important role in these dynamics, by initiating cycles of secondary succession and generating opportunities for communities of long-lived organisms to reorganize in alternative configurations. This study used landscape-scale variations in environmental conditions, stand structure, and disturbance from an extreme fire year in Alaska to examine how these factors affected successional trajectories in boreal forests dominated by black spruce. Because fire intervals in interior Alaska are typically too short to allow relay succession, the initial cohorts of seedlings that recruit after fire largely determine future canopy composition. Consequently, in a dynamically stable landscape, postfire tree seedling composition should resemble that of the prefire forest stands, with little net change in tree composition after fire. Seedling recruitment data from 90 burned stands indicated that postfire establishment of black spruce was strongly linked to environmental conditions and was highest at sites that were moist and had high densities of prefire spruce. Although deciduous broadleaf trees were absent from most prefire stands, deciduous trees recruited from seed at many sites and were most abundant at sites where the fires burned severely, consuming much of the surface organic layer. Comparison of pre- and postfire tree composition in the burned stands indicated that the expected trajectory of black spruce self-replacement was typical only at moist sites that burned with low fire severity. At severely burned sites, deciduous trees dominated the postfire tree seedling community, suggesting these sites will follow alternative, deciduous-dominated trajectories of succession. Increases in the severity of boreal fires with climate warming may catalyze shifts to an increasingly deciduous-dominated landscape, substantially altering landscape dynamics and ecosystem services in this part of the boreal forest. © 2009 Blackwell Publishing Ltd.}, + issue = 4 +} +@misc{jordan1991onedimensional, + title = {A One-dimensional temperature model for a snow cover : technical documentation for SNTHERM.89}, + author = {Rachel E. Jordan}, + year = 1991, + journal = {Special Report 91-16}, + publisher = {Cold Regions Research and Engineering Laboratory (U.S.)}, + url = {http://hdl.handle.net/11681/11677}, + keywords = {Computer models,Mathematical models,SNTHERM.89 (Computer program),Snow,Snow covers,Thermal properties} +} +@article{kelly2016paleodata, + title = {Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests}, + author = {Ryan Kelly and Hélène Genet and A. David McGuire and Feng Sheng Hu}, + year = 2016, + month = 1, + journal = {Nature Climate Change}, + publisher = {Nature Publishing Group}, + volume = 6, + pages = {79--82}, + doi = {10.1038/NCLIMATE2832}, + issn = 17586798, + abstract = {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 predictionsmay 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 showthat firewas the dominant control onC 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 1.4 kg Cm.2 (12% of ecosystem C stocks) from 1950 to 2006. In stark contrast, a small net C sink of 0.3 kg Cm.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.}, + issue = 1 +} +@article{lara2015polygonal, + title = {Polygonal tundra geomorphological change in response to warming alters future CO2 and CH4 flux on the Barrow Peninsula}, + author = {Mark J. Lara and A. David Mcguire and Eugenie S. Euskirchen and Craig E. Tweedie and Kenneth M. Hinkel and Alexei N. Skurikhin and Vladimir E. Romanovsky and Guido Grosse and W. Robert Bolton and Helene Genet}, + year = 2015, + month = 4, + journal = {Global Change Biology}, + publisher = {Blackwell Publishing Ltd}, + volume = 21, + pages = {1634--1651}, + doi = {10.1111/GCB.12757}, + issn = 13652486, + abstract = {The landscape of the Barrow Peninsula in northern Alaska is thought to have formed over centuries to millennia, and is now dominated by ice-wedge polygonal tundra that spans drained thaw-lake basins and interstitial tundra. In nearby tundra regions, studies have identified a rapid increase in thermokarst formation (i.e., pits) over recent decades in response to climate warming, facilitating changes in polygonal tundra geomorphology. We assessed the future impact of 100 years of tundra geomorphic change on peak growing season carbon exchange in response to: (i) landscape succession associated with the thaw-lake cycle; and (ii) low, moderate, and extreme scenarios of thermokarst pit formation (10%, 30%, and 50%) reported for Alaskan arctic tundra sites. We developed a 30 × 30 m resolution tundra geomorphology map (overall accuracy:75%; Kappa:0.69) for our ~1800 km2 study area composed of ten classes; drained slope, high center polygon, flat-center polygon, low center polygon, coalescent low center polygon, polygon trough, meadow, ponds, rivers, and lakes, to determine their spatial distribution across the Barrow Peninsula. Land-atmosphere CO2 and CH4 flux data were collected for the summers of 2006-2010 at eighty-two sites near Barrow, across the mapped classes. The developed geomorphic map was used for the regional assessment of carbon flux. Results indicate (i) at present during peak growing season on the Barrow Peninsula, CO2 uptake occurs at -902.3 106gC-CO2 day-1 (uncertainty using 95% CI is between -438.3 and -1366 106gC-CO2 day-1) and CH4 flux at 28.9 106gC-CH4 day-1(uncertainty using 95% CI is between 12.9 and 44.9 106gC-CH4 day-1), (ii) one century of future landscape change associated with the thaw-lake cycle only slightly alter CO2 and CH4 exchange, while (iii) moderate increases in thermokarst pits would strengthen both CO2 uptake (-166.9 106gC-CO2 day-1) and CH4 flux (2.8 106gC-CH4 day-1) with geomorphic change from low to high center polygons, cumulatively resulting in an estimated negative feedback to warming during peak growing season.}, + issue = 4, + keywords = {Arctic,Carbon balance,Classification,Climate warming,Negative feedback,Polygonal tundra,Thaw-lake cycle,Thermokarst}, + pmid = 25258295 +} +@article{lundin1990hydraulic, + title = {Hydraulic properties in an operational model of frozen soil}, + author = {Lars Christer Lundin}, + year = 1990, + journal = {Journal of Hydrology}, + volume = 118, + pages = {289--310}, + doi = {10.1016/0022-1694(90)90264-X}, + issn = {00221694}, + abstract = {Many current models of heat and water flow in frozen soils overestimate the freezing-induced redistribution of water. These models also treat the soil physical properties as constant in time although they are strongly influenced by the frost itself. This study was conducted to determine possible methods to overcome these two problems in an operational hydraulic model. Winter measurements of soil temperature and water content were performed on a clay soil and on a layered loam soil. The data were compared with simulations made with a physically based, one-dimensional model of coupled heat and water flow. Two procedures were tested for the calculation of hydraulic conductivity of partially frozen soil: firstly, an interpolation procedure, taking into account the strong non-linearity of the hydraulic conductivity function close to the freezing front. Secondly, an impedance parameter was used to describe the effect of ice lenses. A spring time modification of the soil moisture characteristic curve was tested to account for the frost-induced changes of the soil structure. Simulated temperatures and water contents agreed well with measurements, both for the clay and the layered loam soil, after introduction of the impedance parameter. The alternative interpolation procedure did not only reduce the hydraulic conductivity of the frozen soil sufficiently to produce a realistic redistribution, but also enabled use of a lower value on the impedance parameter. Changes in water retention properties resulting from frost action during winter caused an overestimation of simulated water content of 15% by volume in the heavy clay soil during spring. This discrepancy was eliminated by increasing the frequency of pore diameters below 0.1mm in the model during spring. © 1990.}, + issue = {1-4} +} +@article{lyu2018role, + title = {The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska}, + author = {Zhou Lyu and Hélène Genet and Yujie He and Qianlai Zhuang and A. David McGuire and Alec Bennett and Amy Breen and Joy Clein and Eugénie S. Euskirchen and Kristofer Johnson and Tom Kurkowski and Neal J. Pastick and T. Scott Rupp and Bruce K. Wylie and Zhiliang Zhu}, + year = 2018, + month = 9, + journal = {Ecological Applications}, + publisher = {Ecological Society of America}, + volume = 28, + pages = {1377--1395}, + doi = {10.1002/EAP.1755}, + issn = 19395582, + abstract = {Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km2, an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO2) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1-km resolution for the historical period (1950–2009) and future projection period (2010–2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO2 and biogenic methane (CH4) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO2 fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH4 emissions among the simulations (~15% per °C increase). Ecosystem CO2 sequestration offset the increase in CH4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO2, (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH4 emissions to increases in soil temperature.}, + issue = 6, + keywords = {Alaska,Alaska carbon cycle,atmospheric CO2,carbon balance,climate change,fire,global warming potential,methane,wetlands}, + pmid = 29808543 +} +@article{mcguire1992interactions, + title = {Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America}, + author = {A. D. McGuire and J. M. Melillo and L. A. Joyce and D. W. Kicklighter and A. L. Grace and B. Moore and C. J. Vorosmarty}, + year = 1992, + journal = {Global Biogeochemical Cycles}, + volume = 6, + pages = {101--124}, + doi = {10.1029/92GB00219}, + issn = 19449224, + abstract = {We use the terrestrial ecosystem model (TEM), a process‐based model, to investigate how interactions between carbon (C) and nitrogen (N) dynamics affect predictions of net primary productivity (NPP) for potential vegetation in North America. Data on pool sizes and fluxes of C and N from intensively studied field sites are used to calibrate the model for each of 17 non‐wetland vegetation types. We use information on climate, soils, and vegetation to make estimates for each of 11,299 non‐wetland, 0.5° latitude × 0.5° longitude, grid cells in North America. The potential annual NPP and net N mineralization (NETNMIN) of North America are estimated to be 7.032 × 1015 g C yr−1 and 104.6 × 1012 g N yr−1, respectively. Both NPP and NETNMIN increase along gradients of increasing temperature and moisture in northern and temperate regions of the continent, respectively. Nitrogen limitation of productivity is weak in tropical forests, increasingly stronger in temperate and boreal forests, and very strong in tundra ecosystems. The degree to which productivity is limited by the availability of N also varies within ecosystems. Thus spatial resolution in estimating exchanges of C between the atmosphere and the terrestrial biosphere is improved by modeling the linkage between C and N dynamics. We also perform a factorial experiment with TEM on temperate mixed forest in North America to evaluate the importance of considering interactions between C and N dynamics in the response of NPP to an elevated temperature of 2°C. With the C cycle uncoupled from the N cycle, NPP decreases primarily because of higher plant respiration. However, with the C and N cycles coupled, NPP increases because productivity that is due to increased N availability more than offsets the higher costs of plant respiration. Thus, to investigate how global change will affect biosphere‐atmosphere interactions, process‐based models need to consider linkages between the C and N cycles. Copyright 1992 by the American Geophysical Union.}, + issue = 2 +} +@article{mcguire2018assessing, + title = {Assessing historical and projected carbon balance of Alaska: A synthesis of results and policy/management implications}, + author = {A. David McGuire and Hélène Genet and Zhou Lyu and Neal Pastick and Sarah Stackpoole and Richard Birdsey and David D'Amore and Yujie He and T. Scott Rupp and Robert Striegl and Bruce K. Wylie and Xiaoping Zhou and Qianlai Zhuang and Zhiliang Zhu}, + year = 2018, + month = 9, + journal = {Ecological Applications}, + publisher = {Ecological Society of America}, + volume = 28, + pages = {1396--1412}, + doi = {10.1002/EAP.1768}, + issn = 19395582, + abstract = {We summarize the results of a recent interagency assessment of land carbon dynamics in Alaska, in which carbon dynamics were estimated for all major terrestrial and aquatic ecosystems for the historical period (1950–2009) and a projection period (2010–2099). Between 1950 and 2009, upland and wetland (i.e., terrestrial) ecosystems of the state gained 0.4 Tg C/yr (0.1% of net primary production, NPP), resulting in a cumulative greenhouse gas radiative forcing of 1.68 × 10−3 W/m2. The change in carbon storage is spatially variable with the region of the Northwest Boreal Landscape Conservation Cooperative (LCC) losing carbon because of fire disturbance. The combined carbon transport via various pathways through inland aquatic ecosystems of Alaska was estimated to be 41.3 Tg C/yr (17% of terrestrial NPP). During the projection period (2010–2099), carbon storage of terrestrial ecosystems of Alaska was projected to increase (22.5–70.0 Tg C/yr), primarily because of NPP increases of 10–30% associated with responses to rising atmospheric CO2, increased nitrogen cycling, and longer growing seasons. Although carbon emissions to the atmosphere from wildfire and wetland CH4 were projected to increase for all of the climate projections, the increases in NPP more than compensated for those losses at the statewide level. Carbon dynamics of terrestrial ecosystems continue to warm the climate for four of the six future projections and cool the climate for only one of the projections. The attribution analyses we conducted indicated that the response of NPP in terrestrial ecosystems to rising atmospheric CO2 (~5% per 100 ppmv CO2) saturates as CO2 increases (between approximately +150 and +450 ppmv among projections). This response, along with the expectation that permafrost thaw would be much greater and release large quantities of permafrost carbon after 2100, suggests that projected carbon gains in terrestrial ecosystems of Alaska may not be sustained. From a national perspective, inclusion of all of Alaska in greenhouse gas inventory reports would ensure better accounting of the overall greenhouse gas balance of the nation and provide a foundation for considering mitigation activities in areas that are accessible enough to support substantive deployment.}, + issue = 6, + keywords = {Alaska,Alaska carbon cycle,Landscape Conservation Cooperative,boreal forest,climate change,fire,inland aquatic ecosystems,maritime conifer forest,permafrost,tundra,uplands,wetlands}, + pmid = 29923353 +} +@article{merkel2014docker, + title = {Docker: lightweight Linux containers for consistent development and deployment}, + author = {Dirk Merkel}, + year = 2014, + month = 3, + journal = {Linux J.}, + publisher = {Belltown Media}, + volume = 2014, + issn = {1075-3583}, + abstract = {Docker promises the ability to package applications and their dependencies into lightweight containers that move easily between different distros, start up quickly and are isolated from each other.}, + city = {Houston, TX}, + issue = 239 +} +@article{niu2005simple, + title = {A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models}, + author = {Guo Yue Niu and Zong Liang Yang and Robert E. Dickinson and Lindsey E. Gulden}, + year = 2005, + month = 11, + journal = {Journal of Geophysical Research Atmospheres}, + publisher = {Blackwell Publishing Ltd}, + volume = 110, + pages = {1--15}, + doi = {10.1029/2005JD006111}, + issn = {01480227}, + abstract = {This paper develops a simple TOPMODEL-based runoff parameterization (hereinafter SIMTOP) for use in global climate models (GCMs) that improves the runoff production and the partitioning of runoff between surface and subsurface components. SIMTOP simplifies the TOPMODEL runoff formulations in two ways: (1) SIMTOP represents the discrete distribution of the topographic index as an exponential function, not as a three-parameter gamma distribution; this change improves the parameterization of the fractional saturated area, especially in mountainous regions. (2) SIMTOP treats subsurface runoff as a product of an exponential function of the water table depth and a single coefficient, not as a product of several parameters that depend on topography and soil properties; this change facilitates applying TOPMODEL-based runoff schemes on global scale. SIMTOP is incorporated into the National Center for Atmospheric Research (NCAR) Community Land Model version 2.0 (CLM 2.0). SIMTOP is validated at a watershed scale using data from the Sleepers River watershed in Vermont, USA. It is also validated on a global scale using the monthly runoff data from the University of New Hampshire Global Runoff Data Center (UNH-GRDC). SIMTOP performs favorably when compared to the baseline runoff formulation used in CLM2.0. Realistic simulations can be obtained using two distinct saturated hydraulic conductivity (Ksat) profiles. These profiles include (1) exponential decay of Ksat with depth (as is typically done in TOPMODEL-based runoff schemes) and (2) the definition of Ksat using the soil texture profile data (as is typically done in climate models) and the concordant reduction of the gravitational drainage from the bottom of the soil column. Copyright 2005 by the American Geophysical Union.}, + issue = 21 +} +@article{raich1991potential, + title = {Potential net primary productivity in South America: application of a global model}, + author = {J. W. Raich}, + year = 1991, + journal = {Ecological Applications}, + volume = 1, + pages = {399--429}, + doi = {10.2307/1941899}, + issn = 10510761, + abstract = {The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scles. Information from intensively studied field sites is used in combination with continental-scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non-wetland, 0.5° latitude × 0.5° longitude grid cells in South America, at monthly time steps. The potential annual NPP of South America is estimated to be 12.5Pg/yr of carbon (26.3Pg/yr of organic matter) in a non-wetland areas of 17.0×106km2. Over 50% of this production occurs in the tropical and subtropical evergreen forest region. Model runs generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510g.m-2.yr-1 of carbon, with an overall mean of 1170g.m-2.yr-1. Predicted rates of mean annual NPP in other types of vegetation ranged from 95g.m-2.yr-1 in arid shrublands to 930g.m-2.yr-1 in savannas. TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. -from Authors}, + issue = 4 +} +@article{raleigh2013approximating, + title = {Approximating snow surface temperature from standard temperature and humidity data: New possibilities for snow model and remote sensing evaluation}, + author = {Mark S. Raleigh and Christopher C. Landry and Masaki Hayashi and William L. Quinton and Jessica D. Lundquist}, + year = 2013, + month = 12, + journal = {Water Resources Research}, + volume = 49, + pages = {8053--8069}, + doi = {10.1002/2013WR013958}, + issn = {00431397}, + abstract = {Snow surface temperature (Ts) is important to the snowmelt energy balance and landatmosphere interactions, but in situ measurements are rare, thus limiting evaluation of remote sensing data sets and distributed models. Here we test simple Ts approximations with standard height (2-4 m) air temperature (Ta), wet-bulb temperature (Tw), and dew point temperature (Td), which are more readily available than Ts. We used hourly measurements from seven sites to understand which Ts approximation is most robust and how Ts representation varies with climate, time of day, and atmospheric conditions (stability and radiation). Td approximated Ts with the lowest overall bias, ranging from 22.3 to 12.6°C across sites and from 22.8 to 1.5°C across the diurnal cycle. Prior studies have approximated Ts with Ta, which was the least robust predictor of Ts at all sites. Approximation of Ts with Td was most reliable at night, at sites with infrequent clear sky conditions, and at windier sites (i.e., more frequent turbulent instability). We illustrate how mean daily T d can help detect surface energy balance bias in a physically based snowmelt model. The results imply that spatial Td data sets may be useful for evaluating snow models and remote sensing products in data sparse regions, such as alpine, cold prairie, or Arctic regions. To realize this potential, more routine observations of humidity are needed. Improved understanding of Td variations will advance understanding of T s in space and time, providing a simple yet robust measure of snow surface feedback to the atmosphere. © 2013. American Geophysical Union. All Rights Reserved.}, + issue = 12 +} +@article{rew1990netcdf, + title = {NetCDF: An Interface for Scientific Data Access}, + author = {Russ Rew and Glenn Davis}, + year = 1990, + journal = {IEEE Computer Graphics and Applications}, + volume = 10, + doi = {10.1109/38.56302}, + issn = {02721716}, + abstract = {In scientific visualization, two obstacles prevent the full use of heterogeneous networks of powerful workstations: data access and data representation. Low-level sequentialdata access ties visualization applications to application- specific formats. Machine-dependent data representations make it difficult to distribute applications across networks or to display output from programs running on different workstation architectures simultaneously. The Network Common Data Form is a data abstraction for storing and retrieving multidimensional data. MetCDF is distributed as a software library that provides a concrete implementation of that abstraction. The implementation provides a machine-independent format for representing scientific data. Thus NetCDF is more than just another data format. Together, the abstraction, library, and data format support the creation, access, and sharing of scientific information. NetCDF has proven useful for supporting objects that contain dissimilar kinds of data in a heterogeneous network environment and for writing application software that does not depend on application-specific formats. NetCDF data achieve independence from applicationspecific formats because the data are self-describing. This means that a NetCDF data set includes information defining the data it contains. NetCDF data achieve independence from particular machine representations by using a nonproprietary standard for external data representation. Programs that use the NetCDF interface can thus read and write data in a form that is more widely usable than machinedependent binary data files. NetCDF files can provide a way to encapsulate structured scientific data for use among multiple application programs, and thus, these files can help to support high-level data access and shell-level application programming. © 1990 IEEE}, + issue = 4 +} +@article{swenson2012improved, + title = {Improved simulation of the terrestrial hydrological cycle in permafrost regions by the Community Land Model}, + author = {S. C. Swenson and D. M. Lawrence and Hanna Lee}, + year = 2012, + month = 9, + journal = {Journal of Advances in Modeling Earth Systems}, + publisher = {Blackwell Publishing Ltd}, + volume = 4, + doi = {10.1029/2012MS000165}, + issn = 19422466, + abstract = {Plausible predictions of future climate require realistic representations of past and current climate. Simulations of the distribution of permafrost in the 21st century made with the Community Climate System Model (CCSM4) indicate that substantial decreases in permafrost extent can be expected, especially under high emissions scenarios. One of the implications of permafrost loss is the potential release of carbon from newly thawed soils into the atmosphere, thus raising its concentration of greenhouse gases and amplifying the initial warming trend. However, the biogeochemical cycle simulated by CCSM4 presents significant biases in carbon fluxes such as gross primary production, net primary production, and vegetation carbon storage in permafrost regions. The biases in the carbon cycle simulated by CCSM4 are in part due to excessively dry soils in permafrost regions. In this study, we show that the CCSM4 dry soil bias results from the model's formulation of soil hydraulic permeability when soil ice is present. The calculation of the hydraulic properties of frozen soils is first modified by replacing their dependence on total water content with liquid water content only. Then an ice impedance function having a power-law form is incorporated. When the parameterization of the hydraulic properties of frozen soil is corrected, the model simulates significantly higher moisture contents in near-surface soils in permafrost regions, especially during spring. This result is validated qualitatively by comparing soil moisture profiles to descriptions based on field studies, and quantitatively by comparing simulated hydrographs of two large Siberian rivers to observed hydrographs. After the dry soil bias is reduced, the vegetation productivity simulated by the model is improved, which is manifested in leaf area indices that at some locations are twice as large as in the original model. © 2012. American Geophysical Union.}, + issue = 8 +} +@article{tian1999sensitivity, + title = {The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States}, + author = {H. TIAN and J. M. MELILLO and D. W. KICKLIGHTER and A. D. McGUIRE and J. HELFRICH}, + year = 1999, + month = 4, + journal = {Tellus B}, + publisher = {Stockholm University Press}, + volume = 51, + pages = {414--452}, + doi = {10.1034/J.1600-0889.1999.00021.X}, + issn = {0280-6509}, + abstract = {We use the Terrestrial Ecosystem Model (TEM, Version 4.1) and the land cover data set of the international geosphere–biosphere program to investigate how increasing atmospheric CO2 concentration and climate variability during 1900–1994 affect the carbon storage of terrestrial ecosystems in the conterminous USA, and how carbon storage has been affected by land-use change. The estimates of TEM indicate that over the past 95 years a combination of increasing atmospheric CO2 with historical temperature and precipitation variability causes a 4.2% (4.3 Pg C) decrease in total carbon storage of potential vegetation in the conterminous US, with vegetation carbon decreasing by 7.2% (3.2 Pg C) and soil organic carbon decreasing by 1.9% (1.1 Pg C). Several dry periods including the 1930s and 1950s are responsible for the loss of carbon storage. Our factorial experiments indicate that precipitation variability alone decreases total carbon storage by 9.5%. Temperature variability alone does not significantly affect carbon storage. The effect of CO2 fertilization alone increases total carbon storage by 4.4%. The effects of increasing atmospheric CO2 and climate variability are not additive. Interactions among CO2, temperature and precipitation increase total carbon storage by 1.1%. Our study also shows substantial year-to-year variations in net carbon exchange between the atmosphere and terrestrial ecosystems due to climate variability. Since the 1960s, we estimate these terrestrial ecosystems have acted primarily as a sink of atmospheric CO2 as a result of wetter weather and higher atmospheric CO2 concentrations. For the 1980s, we estimate the natural terrestrial ecosystems, excluding cropland and urban areas, of the conterminous US have accumulated 78.2 Tg C yr−1 because of the combined effect of increasing atmospheric CO2 and climate variability. For the conterminous US, we estimate that the conversion of natural ecosystems to cropland and urban areas has caused a 18.2% (17.7 Pg C) reduction in total carbon storage from that estimated for potential vegetation. The carbon sink capacity of natural terrestrial ecosystems in the conterminous US is about 69% of that estimated for potential vegetation.}, + issue = 2 +} +@article{walter2000processbased, + title = {A process-based, climate-sensitive model to derive methane emissions from natural wetlands: Application to five wetland sites, sensitivity to model parameters, and climate}, + author = {Bernadette P. Walter and Martin Heimann}, + year = 2000, + journal = {Global Biogeochemical Cycles}, + volume = 14, + pages = {745--765}, + doi = {10.1029/1999GB001204}, + issn = {08866236}, + abstract = {Methane emissions from natural wetlands constitute the largest methane source at present and depend highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a one-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a one-dimensional soil column and the three different transport mechanisms, diffusion, plant-mediated transport, and ebullition, are modeled explicitly. The model forcing consists of daily values of soil temperature, water table, and net primary productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at five wetland sites located in North America, Europe, and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to longer-term climate variations.}, + issue = 3 +} +@article{woo2004twodirectional, + title = {A two-directional freeze and thaw algorithm for hydrologic and land surface modelling}, + author = {M. K. Woo and M. A. Arain and M. Mollinga and S. Yi}, + year = 2004, + month = 6, + journal = {Geophysical Research Letters}, + volume = 31, + doi = {10.1029/2004GL019475}, + issn = {00948276}, + abstract = {This paper presents a two-directional Stefan's solution for computing the freeze and thaw of soil columns. Use of an inverted set of equations to drive the soil freeze-thaw from the bottom is a significant improvement to the original freeze-thaw model. Simulations using the algorithm compared well with the 0°C isotherm interpolated from observed data at Arctic, Subarctic and cool temperate sites with different frost conditions that range from permafrost to seasonal frost across a north-south gradient in North America. The incorporation of explicit freeze-thaw parameterization in hydrologic and land surface models would enable realistic simulation of soil temperature, soil moisture and runoff/infiltration and hence energy, water and greenhouse gas exchange processes in high latitudes. Copyright 2004 by the American Geophysical Union.}, + issue = 12 +} +@article{yi2009interactions, + title = {Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance}, + author = {Shuhua Yi and A. David McGuire and Jennifer Harden and Eric Kasischke and Kristen Manies and Larry Hinzman and Anna Liljedahl and Jim Randerson and Heping Liu and Vladimir Romanovsky and Sergei Marchenko and Yongwon Kim}, + year = 2009, + month = 6, + journal = {Journal of Geophysical Research: Biogeosciences}, + publisher = {Blackwell Publishing Ltd}, + volume = 114, + doi = {10.1029/2008JG000841}, + issn = {01480227}, + abstract = {Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postbura measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in modeldata comparison, the model demonstrates substantial ability in simulating the dynamics of évapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity. Copyright 2009 by the American Geophysical Union.}, + issue = 2 +} +@article{yi2010dynamic, + title = {A dynamic organic soil biogeochemical model for simulating the effects of wildfire on soil environmental conditions and carbon dynamics of black spruce forests}, + author = {Shuhua Yi and A. David McGuire and Eric Kasischke and Jennifer Harden and Kristen Manies and Michelle MacK and Merritt Turetsky}, + year = 2010, + month = 12, + journal = {Journal of Geophysical Research: Biogeosciences}, + publisher = {Blackwell Publishing Ltd}, + volume = 115, + doi = {10.1029/2010JG001302}, + issn = {01480227}, + abstract = {Ecosystem models have not comprehensively considered how interactions among fire disturbance, soil environmental conditions, and biogeochemical processes affect ecosystem dynamics in boreal forest ecosystems. In this study, we implemented a dynamic organic soil structure in the Terrestrial Ecosystem Model (DOS-TEM) to investigate the effects of fire on soil temperature, moisture, and ecosystem carbon dynamics. DOS-TEM consists of environmental, ecological, disturbance effects, and dynamic organic soil modules. Changes in organic layer thickness are computed from calculated changes in carbon pools following fire and during stand succession. DOS-TEM was parameterized based on studies reported in the literature and evaluated independently at sites in interior Alaska. This evaluation reveals that (1) DOS-TEM is capable of accurately simulating the thickness and carbon content of organic soils; and (2) without the dynamic linkage between soil organic thickness and carbon content, the model overestimates soil carbon in deep mineral soil horizons of dry black spruce ecosystems of interior Alaska. Sensitivity tests were performed to investigate issues related to spatial heterogeneity of carbon dynamics including soil drainage and fire frequency. Results show that both soil drainage and fire frequency are important in the carbon dynamics simulated by DOS-TEM, and should be considered in spatial applications of the model. Copyright © 2010 by the American Geophysical Union.}, + issue = 4 +} +@article{yuan2012assessment, + title = {Assessment of boreal forest historical C dynamics in the Yukon River Basin: Relative roles of warming and fire regime change}, + author = {F. M. Yuan and S. H. Yi and A. D. Mcguire and K. D. Johnson and J. Liang and J. W. Harden and E. S. Kasischke and W. A. Kurz}, + year = 2012, + month = 12, + journal = {Ecological Applications}, + volume = 22, + pages = {2091--2109}, + doi = {10.1890/11-1957.1}, + issn = 10510761, + abstract = {Carbon (C) dynamics of boreal forest ecosystems have substantial implications for efforts to mitigate the rise of atmospheric CO2 and may be substantially influenced by warming and changing wildfire regimes. In this study we applied a large-scale ecosystem model that included dynamics of organic soil horizons and soil organic matter characteristics of multiple pools to assess forest C stock changes of the Yukon River Basin (YRB) in Alaska, USA, and Canada from 1960 through 2006, a period characterized by substantial climate warming and increases in wildfire. The model was calibrated for major forests with data from long-term research sites and evaluated using a forest inventory database. The regional assessment indicates that forest vegetation C storage increased by 46 Tg C, but that total soil C storage did not change appreciably during this period. However, further analysis suggests that C has been continuously lost from the mineral soil horizon since warming began in the 1970s, but has increased in the amorphous organic soil horizon. Based on a factorial experiment, soil C stocks would have increased by 158 Tg C if the YRB had not undergone warming and changes in fire regime. The analysis also identified that warming and changes in fire regime were approximately equivalent in their effects on soil C storage, and interactions between these two suggests that the loss of organic horizon thickness associated with increases in wildfire made deeper soil C stocks more vulnerable to loss via decomposition. Subbasin analyses indicate that C stock changes were primarily sensitive to the fraction of burned forest area within each subbasin and that boreal forest ecosystems in the YRB are currently transitioning from being sinks to sources at ;0.7% annual area burned. We conclude that it is important for international mitigation efforts focused on controlling atmospheric CO2 to consider how climate warming and changes in fire regime may concurrently affect the CO 2 sink strength of boreal forests. It is also important for large-scale biogeochemical and earth system models to include organic soil dynamics in applications to assess regional C dynamics of boreal forests responding to warming and changes in fire regime. © 2012 by the Ecological Society of America.}, + issue = 8, + keywords = {Assessment,Basin-scale analysis,Boreal forests,C stock dynamics,Climate warming,Dynamic organic soil,Fire regime change,Terrestrial ecological modeling}, + pmid = 23387112 +} +@article{zhuang2003carbon, + title = {Carbon cycling in extratropical terrestrial ecosystems of the Northern Hemisphere during the 20th century: a modeling analysis of the influences of soil thermal dynamics}, + author = {Q. Zhuang and A. D. McGuire and J. M. Melillo and J. S. Clein and R. J. Dargaville and D. W. Kicklighter and R. B. Myneni and J. Dong and V. E. Romanovsky and J. Harden and J. E. Hobbie}, + year = 2003, + month = 1, + journal = {Tellus B: Chemical and Physical Meteorology}, + publisher = {Stockholm University Press}, + volume = 55, + pages = 751, + doi = {10.3402/TELLUSB.V55I3.16368}, + issn = {0280-6509}, + abstract = {There is substantial evidence that soil thermal dynamics are changing in terrestrial ecosystems of the Northern Hemisphere and that these dynamics have implications for the exchange of carbon betwe...}, + issue = 3 +} +@article{zhuang2003modeling, + title = {Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska}, + author = {Q. Zhuang and A. D. McGuire and K. P. O'Neill and J. W. Harden and V. E. Romanovsky and J. Yarie}, + year = 2003, + month = 1, + journal = {Journal of Geophysical Research: Atmospheres}, + publisher = {Blackwell Publishing Ltd}, + volume = 108, + doi = {10.1029/2001JD001244}, + issn = {01480227}, + abstract = {In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce ecosystem in Canada, the age-dependent pattern of the simulated vegetation carbon was verified with inventory data on aboveground growth of Alaskan black spruce forests, and the model was applied to a postfire chronosequence in interior Alaska. The comparison between the simulated soil temperature and field-based estimates during the growing season (May to September) of 1997 revealed that the model was able to accurately simulate monthly temperatures at 10 cm (R > 0.93) for control and burned stands of the fire chronosequence. Similarly, the simulated and field-based estimates of soil respiration for control and burned stands were correlated (R = 0.84 and 0.74 for control and burned stands, respectively). The simulated and observed decadal to century-scale dynamics of soil temperature and carbon dynamics, which are represented by mean monthly values of these variables during the growing season, were correlated among stands (R = 0.93 and 0.71 for soil temperature at 20- and 10-cm depths, R = 0.95 and 0.91 for soil respiration and soil carbon, respectively). Sensitivity analyses indicate that along with differences in fire and climate history a number of other factors influence the response of carbon dynamics to fire disturbance. These factors include nitrogen fixation, the growth of moss, changes in the depth of the organic layer, soil drainage, and fire severity.}, + issue = 1, + keywords = {Carbon,Fire,Hydrology,Nitrogen,Permafrost} +} +@article{zhuang2004methane, + title = {Methane fluxes between terrestrial ecosystems and the atmosphere at northern high latitudes during the past century: A retrospective analysis with a process-based biogeochemistry model}, + author = {Q. Zhuang and J. M. Melillo and D. W. Kicklighter and R. G. Prinn and A. D. McGuire and P. A. Steudler and B. S. Felzer and S. Hu}, + year = 2004, + month = 9, + journal = {Global Biogeochemical Cycles}, + volume = 18, + doi = {10.1029/2004GB002239}, + issn = {08866236}, + abstract = {We develop and use a new version of the Terrestrial Ecosystem Model (TEM) to study how rates of methane (CH4) emissions and consumption in high-latitude soils of the Northern Hemisphere have changed over the past century in response to observed changes in the region's climate. We estimate that the net emissions of CH4 (emissions minus consumption) from these soils have increased by an average 0.08 Tg CH4 yr-1 during the twentieth century. Our estimate of the annual net emission rate at the end of the century for the region is 51 Tg CH4 yr-1. Russia, Canada, and Alaska are the major CH4 regional sources to the atmosphere, responsible for 64%, 11%, and 7% of these net emissions, respectively. Our simulations indicate that large interannual variability in net CH4 emissions occurred over the last century. Our analyses of the responses of net CH4 emissions to the past climate change suggest that future global warming will increase net CH4 emissions from the Pan-Arctic region. The higher net CH4 emissions may increase atmospheric CH 4 concentrations to provide a major positive feedback to the climate system. Copyright 2004 by the American Geophysical Union.}, + issue = 3, + keywords = {Methane emissions,Methane oxidation,Permafrost} +} diff --git a/docs_src/sphinx/source/conf.py b/docs_src/sphinx/source/conf.py index 26a09d36..1c422905 100644 --- a/docs_src/sphinx/source/conf.py +++ b/docs_src/sphinx/source/conf.py @@ -31,6 +31,9 @@ # -- General configuration --------------------------------------------------- +numfig = True # auto-numbering for figures, reference by name + + # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. @@ -45,8 +48,11 @@ #'numpydoc', 'sphinx.ext.napoleon', 'sphinxarg.ext', + 'sphinxcontrib.bibtex', ] +bibtex_bibfiles = ["bibliography.bib"] +bibtex_reference_style = "author_year" # -- Config for some extensions ---------------------------------------------- autosectionlabel_prefix_document = True diff --git a/docs_src/sphinx/source/images/dvmdostem-general-pixel_export_2024-15-11.jpg b/docs_src/sphinx/source/images/dvmdostem-general-pixel_export_2024-15-11.jpg new file mode 100644 index 00000000..a1082ec3 Binary files /dev/null and b/docs_src/sphinx/source/images/dvmdostem-general-pixel_export_2024-15-11.jpg differ diff --git a/docs_src/sphinx/source/images/dvmdostem-overview-export_2024-08-19.jpg b/docs_src/sphinx/source/images/dvmdostem-overview-export_2024-08-19.jpg new file mode 100644 index 00000000..d1dc2470 Binary files /dev/null and b/docs_src/sphinx/source/images/dvmdostem-overview-export_2024-08-19.jpg differ diff --git a/docs_src/sphinx/source/model_overview.rst b/docs_src/sphinx/source/model_overview.rst index c89a9ef0..0a9a84ee 100644 --- a/docs_src/sphinx/source/model_overview.rst +++ b/docs_src/sphinx/source/model_overview.rst @@ -10,119 +10,197 @@ Model Overview ############## -.. raw:: html +`DVMDOSTEM` is designed to simulate the key biophysical and biogeochemical +processes between the soil, the vegetation and the atmosphere. The evolution and +refinement of `DVMDOSTEM` have been shaped by extensive research programs and +applications both in permafrost and non-permafrost regions +(:cite:p:`genet2013modeling`; :cite:p:`genet2018role`; +:cite:p:`jafarov2013effects`; :cite:p:`yi2010dynamic`; +:cite:p:`yi2009interactions`; :cite:p:`euskirchen2022assessing`; +:cite:p:`briones2024exploring`). The model is spatially explicit and represents +ecosystem response to climate and disturbances at seasonal (i.e. monthly) to +centennial scales. The snow and soil columns are split into a dynamic number of +layers to represent their impact on thermal and hydrological dynamics and the +consequences for soil C and N dynamics. Vegetation composition is modeled using +community types (CMTs), each of which consists of multiple plant functional +types (PFTs - groups of species sharing similar ecological traits). This +structure allows the model to represent the effect of competition for light, +water and nutrients on vegetation composition :cite:p:`euskirchen2009changes`, +as well as the role of nutrient limitation on permafrost ecosystem dynamics, +with coupling between C and N cycles (:cite:p:`mcguire1992interactions`; +:cite:p:`euskirchen2009changes`). Finally, the model represents the effects of +wildfire in order to evaluate the role of climate-driven fire intensification on +ecosystem structure and function(:cite:p:`yi2010dynamic`; +:cite:p:`genet2013modeling`). The structure of `DVMDOSTEM` is represented +visually in :numref:`Fig. %s ` . + +.. See shared drive, "Documentation Embed Images > dvmdostem-overview" +.. figure:: images/dvmdostem-overview-export_2024-08-19.jpg + :name: modeloverview + :alt: Visual overview of DVMDOSTEM. + + Overview of `DVMDOSTEM` soil and vegetation structure. On the left is the + soil structure showing the layers and different properties that are tracked + (purple bubble: carbon (C), nitrogen (N), temperature (T), volumetric water + content (VWC), ice). Each of the layers with properties described above is + also categorized as organic (fibric or humic) or mineral. Additionally, the + model simulates snow layers and the removal of soil organic layers due to + fire. On the right is the vegetation structure showing plant functional + types (PFTs) within a community type (CMT) and the associated pools and + fluxes of C and N. Each PFT is split into compartments (leaf, stem and root) + which track their own C and N content and associated fluxes. The fluxes are + represented with red text while the pools are black. In addition, there is + competition among the PFTs for light, water, and available N, shown with the + purple arrow in the top center. + - - - ********* Structure ********* -`dvmdostem` is multi-dimensional. It operates across spatial and temporal +`DVMDOSTEM` is multi-dimensional. It operates across spatial and temporal dimensions, soil layers, and plant functional types. +.. See shared drive "Documentation Embed Images > dvmdostem-general-pixel" +.. figure:: images/dvmdostem-general-pixel_export_2024-15-11.jpg + :name: dvmdostem-pixel-overview + :alt: Visual overview of DVMDOSTEM pixel + + DVMDOSTEM is a spatially explicit. The base unit of computation is a pixel. + There pixels are laid out in a grid. Each pixel is run based on the status + of a run mask, which is one of the required input files. Each pixel is + parameterized for both soil and vegetation properties. Together the + parameterizaton values define a Community Type (CMT). Each pixel is modeled + using Plant Functional Types (PFTs) and a layer stack for soil and snow. + + ======= Spatial ======= -TEM is a spatially explicit model. The run domain is divided into grid cells, -or pixels. There is no communication between the grid cells. TEM itself is -agnostic to the spatial resolution - the resolution is controlled by the -input files provided. Recent work has been done with 1km spatial resolution. +`DVMDOSTEM` can be applied at the site level or across large regions. Spatially, +`DVMDOSTEM` breaks up the landscape into grid cells, each of which is +characterized by a set of input forcing and parameterization values. Gridded +parameterization values describe soil and vegetation characteristics associated +with each Community Type (CMT). `DVMDOSTEM` does not include the lateral +transfer of information between grid cells. The CMT classification for each grid +cell is static across the time dimension of a model simulation. These two +factors limit the ability of the model to represent climate-driven biome shifts +or succession trajectories from disturbances such as wildfire +:cite:p:`johnstone2010changes`. Design discussions are in progress for adding +these capabilities to `DVMDOSTEM`. + +`DVMDOSTEM` itself is agnostic to the spatial resolution - the resolution is +controlled by the input files provided. Recent work has been done with 1km +spatial resolution. + ======== Temporal ======== -TEM is a temporal model in the sense that a run operates processes at consecutive -time-steps. In addition, with TEM, the concept of a "run stage" is used to run -the model over different climatic periods of generally increasing complexity. -There are 5 possible “run stages”: - -* Pre-run (pr) -* Equilibrium (eq) -* Spinup (sp) -* Transient (tr) -* Scenario (sc) - -The primary difference between the run stages is the nature of the input climate -dataset, and specifically whether there is annual variability in the driving -climate data that the model uses. A complete, future-projecting, simulation is -usually only made after advancing the model through several of the previous run -stages to stabilize the system. Typically the ending state from each stage is -used as the beginning state for each subsequent stage. - -A complete run utilizes all 5 stages. It is possible to work with any subset of -the stages. - ------------- -pre-run (pr) ------------- - -The pre-run is an equilibrium run for the physical variables of the model. It is -typically 100 years, uses constant climate (typically monthly average computed -from the [1901-1930] period). - - ----------------- -equilibrium (eq) ----------------- -In the equilibrium stage, the climate is fixed. That is, the climate does not -vary from year to year. There will be intra-annual variability to represent the -seasons, but from year to year the calculations will be carried out using the -same annual cycles. Equilibrium run stage is used in the calibration mode, -and is typically the first stage run for any complete simulation. During the -eq stage, the annual climate inputs used are actually calculated as the mean -of the first 30 years of the historic climate dataset, so the mean of the -values from 1901-1930. - -.. note:: Automatic equilibrium detection. - TEM does not have an internal test for whether or not equilibrium has - been reached. In other words, if you specify ``--max-eq=20000``, the model - will run for 20,000 years no matter what internal state it reached. It - appears that some of the variable and constant names and the command - line flag ``--max-eq`` are vestigial remains of an attempt at "automatic - equilibrium detection". - ------------ -spinup (sp) ------------ -In the spinup stage, the climate is not fixed. In the sp stage, the driving -climate is used from the first 30 years of the historic climate dataset. Should -the spstage be set to run longer than 30 years, the 30 year climate period is -re-used. Another difference between eq and sp stages is that the sp stage is set -to run for a fixed number of years, regardless of the internal state that the -model reaches. In the sp stage the fire date is fixed, occuring at an interval -equal to the Fire Recurrence Interval (FRI). - --------------- -transient (tr) --------------- -In the transient stage, the climate varies from year to year. The tr stage is -used to run the model over the period of historical record. The input climate -data for the tr stage should be the historic climate. This is typically the -climate data for the 20th century, so roughly 1901-2009. - --------------- -scenario (sc) --------------- -In the scenario stage, the climate also varies from year to year, but rather -than observed variability, a predicted climate scenario is used. - -A complete run utilizes all 5 stages. It is possible to work with any subset of -the stages + +`DVMDOSTEM` is a temporal model: a run consists of executing the ecologic +processes through consecutive time-steps. Much of the modeling is occurring at +a monthly time step, although some process execute at a daily resolution and +some processes are yearly. + +To initialize historical or future simulations, `DVMDOSTEM` needs to compute a +quasi steady-state (QSS) solution. This solution is forced by using averaged +historical atmospheric and ecosystem properties (e.g. soil texture) to drive the +model. QSS of physical processes (e.g. soil temperature and water content) are +usually achieved in less than 100 years, while QSS of biogeochemical processes +(e.g. soil and vegetation :math:`C` and :math:`N` stocks) are achieved in 1,000 +to >10,000 years. However, to decrease overall run-times, `DVMDOSTEM` uses two +QSS stages: “Pre-run” and “Equilibrium”. The list of all `DVMDOSTEM` run stages +is as follows: + +* Pre-run (pr): QSS computation for the physical state variables. +* Equilibrium (eq): QSS computation for the biogeochemical state variables. +* Spinup (sp): introduction of pre-industrial climate variability and fire + regime. +* Transient (tr): historical simulation. +* Scenario (sc): future simulation. + +Model simulation requires advancing the model consecutively through all of the +run stages as needed (``pr -> eq -> sp -> tr ->``). It is possible to work with +any subset of the stages using the command line ``--restart`` flag. + +.. note:: Automatic equilibrium (QSS) detection. + + `DVMDOSTEM` does not have an internal test for whether or not equilibrium + (quasi steady state; QSS) has been reached. In other words, if you specify + ``--max-eq=20000``, the model will run for 20,000 years no matter what + internal state it reached. It appears that some of the variable and constant + names and the command line flag ``--max-eq`` are vestigial remains of an + attempt at "automatic equilibrium detection". + + +.. collapse:: pre-run (pr) + + The pre-run is an equilibrium run for the physical variables of the model. + It is typically 100 years, uses constant climate (typically monthly average + computed from the [1901-1930] period). + + +.. collapse:: equilibrium (eq) + + In the equilibrium stage, the climate is fixed. That is, the climate does + not vary from year to year. There will be intra-annual variability to + represent the seasons, but from year to year the calculations will be + carried out using the same annual cycles. Equilibrium run stage is used in + the calibration mode, and is typically the first stage run for any complete + simulation. During the eq stage, the annual climate inputs used are actually + calculated as the mean of the first 30 years of the historic climate dataset + (specified in the config file), so the mean of the values from 1901-1930. + + +.. collapse:: spinup (sp) + + In the spinup stage, the climate is not fixed: the driving climate is used + from the first 30 years of the historic climate dataset. Should the spstage + be set to run longer than 30 years, the 30 year climate period is re-used. + In the sp stage the fire date is fixed, occuring at an interval equal to the + Fire Recurrence Interval (FRI). + + +.. collapse:: transient (tr) + + In the transient stage, the climate varies from year to year. The tr stage + is used to run the model over the period of historical record. The input + climate data for the tr stage should be the historic climate. This is + typically the climate data for the 20th century, so roughly 1901-2009. + + +.. collapse:: scenario (sc) + + In the scenario stage, the climate also varies from year to year, but rather + than observed variability, a predicted climate scenario is used. ======================= Community Types (CMTs) ======================= -Each TEM grid cell can be assigned one “community type” (CMT). A community -type is essentially a parameterization that specifies many properties for -vegetation, and soil. +Each `DVMDOSTEM` grid cell can be assigned one “community type” (CMT). A +community type is essentially a parameterization that specifies many properties +for vegetation, and soil. ======================= Vegetation Types (PFTs) ======================= - WRITE THIS... +Each vegetation CMT (e.g. “wet-sedge tundra”, “white spruce forest”, etc.), is +modeled with up to ten PFTs (e.g., “deciduous shrubs”, “sedges”, “mosses”), each +of which may have up to three compartments: leaf, stem, and root. Vegetation +:math:`C` and :math:`N` fluxes are calculated at each time step based on +environmental factors and soil properties. Assimilation of atmospheric +:math:`CO_2` by the vegetation is estimated by computing gross primary +productivity (GPP) for each PFT. GPP is a function of foliage development +(seasonal and successional patterns), air and soil temperature, water and +nutrient availability, photosynthetically active radiation, and maximum +assimilation rate (a calibrated parameter) (:cite:p:`mcguire1992interactions`; +:cite:p:`euskirchen2009changes`). Changes in vegetation :math:`C` stocks are +calculated using GPP, autotrophic respiration (Ra), and litter-fall (transfer +from vegetation to soil). Vegetation :math:`N` stocks are calculated using plant +:math:`N` uptake and litter-fall. Vegetation :math:`C` and :math:`N` stocks may +also be modified as a result of wildfire burn. .. raw:: html @@ -130,9 +208,29 @@ Vegetation Types (PFTs) ======================= -Soil (Layers) +Soil and Snow (Layers) ======================= - WRITE THIS... + +The soil column is structured as a sequence of layers organized by soil horizons +(i.e. fibric, humic, mineral, and parent material). The number and physical +properties of layers may change throughout the simulation based on vegetation, +thermal, hydrologic, and seasonal properties that are calculated at each time +step (:cite:p:`zhuang2003modeling`; :cite:p:`euskirchen2014changes`; +:cite:p:`yi2009interactions`; :cite:p:`mcguire2018assessing`). The model uses +the two-directional Stefan algorithm to predict freezing/thawing fronts and the +Richards equation to predict soil moisture dynamics in the unfrozen layers +(:cite:p:`yi2009interactions`; :cite:p:`yi2010dynamic`; +:cite:p:`zhuang2003modeling`). Snow is also represented with a dynamic stack of +layers. The physical properties of the snowpack (density, thickness, and +temperature) are calculated from snowfall, sublimation and snowmelt. Snow cover +influences soil-thermal and hydrological seasonal dynamics. Changes in soil +:math:`C` stocks are a result of litter-fall from the vegetation and +decomposition of soil :math:`C` stocks by microbes (heterotrophic respiration or +Rh). Changes in soil organic and available :math:`N` stocks are a result of +litter-fall, net mineralization of organic :math:`N` , and plant :math:`N` +uptake. Soil organic layers and soil :math:`C` and :math:`N` stocks may also be +modified due to wildfire. + .. raw:: html @@ -142,55 +240,28 @@ Soil (Layers) -*********** -Processes -*********** - WRITE THIS... - -========== -Carbon -========== - WRITE THIS... - -========== -Water -========== - WRITE THIS... - -========== -Nitrogen -========== - WRITE THIS... - -================= -Energy Balance -================= - WRITE THIS... - -========== -Permafrost -========== - WRITE THIS... - -============== -Disturbance -============== - WRITE THIS... -========== -Methane -========== - WRITE THIS... ********************* Inputs/Outputs (IO) ********************* +NetCDF files :cite:p:`rew1990netcdf` are used as model inputs and outputs, +conforming to the CF Conventions v1.11 :cite:p:`eaton2011netcdf` where possible. + ======== Inputs ======== +The input variables used to drive `DVMDOSTEM` include: drainage classification +(upland or lowland), CMT classification, topography (slope, aspect, elevation), +soil texture (percent sand, silt, and clay), climate (air temperature, +precipitation, vapor pressure, incoming shortwave radiation), atmospheric +:math:`CO_2` concentration, and fire occurrence (date and severity). All input +datasets are spatially explicit, except the time series of atmospheric +:math:`CO_2`. + Generally TEM requires several types of inputs: * Spatially explicit - varies over spatial dimensions. @@ -356,71 +427,71 @@ The complete list of required TEM input variables is shown below. Outputs ========== +There are approximately 110 different variables available for output from +`DVMDOSTEM`. One file will be produced per requested output variable. Users can +specify the temporal and structural resolutions at which model outputs are +produced. This functionality allows users to consider their computational +resources and information needs when setting up a model run. + The outputs that are available for DVM-DOS-TEM are listed in the -``config/output_spec.csv`` file that is shipped ith the repo. The following table -is built from that csv file: +``config/output_spec.csv`` file that is shipped with the repo. The following +table is built from that csv file: +.. hint:: Wide table, scroll right to see all columns! .. csv-table:: output_spec.csv :file: ../../../config/output_spec.csv :header-rows: 1 ------------------- -Output Selection ------------------- - WRITE THIS... - -.. note:: draft thoughts: - NetCDF outputs are specified in a csv file named in config/config.js. The - csv file specifies a variable name (for identification only - it does not - correspond to the variable name in the code), a short description, units, - and what level of detail to output on (timestep and variable part). - [Link to default file after PR merge] Variable name, Description, - Units, Yearly, Monthly, Daily, PFT, Compartment, Layer, - Example entry: VEGC,Total veg. biomass C,gC/m2,y,m,,p,c,, - This will output VegC every month, and provide both PFT and PFT - compartment values. - The file is more user-friendly when viewed in a spreadsheet. - [example] - A complete list of output combinations is below - The initial list of outputs can be found at Issue #252 - LAYERDEPTH, LAYERDZ, and LAYERTYPE should be automatically output if - the user specifies any by-layer output. They are not currently, so ensure - that they are specified on the same timestep as the desired output. - HKLAYER, LAYERDEPTH, LAYERDZ, LAYERTYPE, TCLAYER, TLAYER, and VWCLAYER - must have the layer option specified or they will generate NetCDF - dimension bound errors. - - -------------- -Process -------------- - WRITE THIS... - -.. note:: draft thoughts: - A single output file will be produced for each entry in the specifying file, - based on variable name, timestep, and run stage. - VEGC_monthly_eq.nc - At the beginning of the model run, an output file will be constructed for each - variable specified, for each run stage where NetCDF output is indicated and that - has more than 0 years of run time. - Currently the model tracks the variables specified for each timestep as separate - sets (i.e. monthly separate from yearly, etc). This reduces the number of map - lookups every time the output function is called, but increases the number of - monthly vs. yearly string comparisons. - ------------------------------- -Variable Output Combinations ------------------------------- - WRITE THIS... - -.. note:: draft thoughts: - '-' indicates that the combination is not an option 'x' indicates that the - combination has been implemented in the code '?' indicates that it is undecided - if the combination should be made available, or that structure in the code needs - to be modified to make data available for output. - Three variables should be automatically written out if any by-layer variable is - specified: Layer type Layer depth Layer thickness Currently they are written out - like standard variables. Automation will need to be added in the future. - +******************** +Parameterization +******************** + +`DVMDOSTEM` parameterization sets are developed for each CMT. Each CMT is +defined by more than 200 parameters. Parameter values are estimated directly +from field, lab or remote sensing observations, literature review or +site-specific calibration. Calibration is required when (1) parameter values +cannot be determined directly from available data or published information, and +(2) model sensitivity to the parameter is substantial. The calibration process +consists of adjusting parameter values until there is acceptable agreement +between measured field data and model prediction on the state variables most +influenced by the parameter to be calibrated. Due to the large number of +parameters requiring calibration, and the non-linear nature of the relationships +between parameters and state variables, model calibration can be +labor-intensive. We are actively developing a calibration process that allows +automation :cite:p:`jafarovINPREP2024`. + +****************** +Software Design +****************** + +The `DVMDOSTEM` software repository is a combination of tightly coupled +sub-components: + + - the `DVMDOSTEM` model, + - supporting tools, and + - development environment specifications. + +The core `DVMDOSTEM` model is written in C++ and uses some object-oriented concepts. +The model exposes a command line interface that allows users to start simulations +manually or use a scripting language to drive the command line interface. + +Surrounding the core model is a large body of supporting tools to assist the +user with preparing inputs, setting up and monitoring model runs and analyzing +model outputs. This collection of tools is primarily written in Python and shell +scripts, with some of the demonstration and exploratory analysis using Jupyter +Notebooks. The supporting tooling is partially exposed via command line +interfaces and a Python API which are documented in the User Guide. + +The model and tools target a UNIX-like operating system environment. The +combination of the core `DVMDOSTEM` model and the supporting tools result in the +need for a complex computing environment with many dependencies. Docker images +are used to manage this complexity, providing consistent environments +for development and production, :cite:p:`merkel2014docker`. + +Software updates are ongoing, stemming from the organic growth spanning 30+ years +of development by research scientists, graduate students and programmers. Recent +years have seen an increased effort to apply professional software development +practices such as version control, automated documentation, containerization, +and testing. \ No newline at end of file diff --git a/docs_src/sphinx/source/references.rst b/docs_src/sphinx/source/references.rst index d7b33c7b..4edf89dd 100644 --- a/docs_src/sphinx/source/references.rst +++ b/docs_src/sphinx/source/references.rst @@ -9,219 +9,6 @@ References ################ -.. Formatting follows the Ecological Applications style - -Balshi, M. S., A. D. McGuire, Q. Zhuang, J. Melillo, D. W. Kicklighter, E. -Kasischke, C. Wirth, M. Flannigan, J. Harden, J. S. Clein, T. J. Burnside, J. -McAllister, W. A. Kurz, M. Apps, and A. Shvidenko. 2007. The role of -historical fire disturbance in the carbon dynamics of the pan-boreal region: -A process-based analysis. Journal of Geophysical Research: Biogeosciences -112. -https://doi.org/10.1029/2006JG000380 - -Balshi, M. S., A. D. Mcguire, P. Duffy, M. 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McGuire, J. Harden, E. Kasischke, K. Manies, L. Hinzman, A. -Liljedahl, J. Randerson, H. Liu, V. Romanovsky, S. Marchenko, and Y. Kim. -2009. Interactions between soil thermal and hydrological dynamics in the -response of Alaska ecosystems to fire disturbance. Journal of Geophysical -Research-Biogeosciences 114:G02015. -https://doi.org/10.1029/2008jg000841 - -Yi, S., A. D. McGuire, E. Kasischke, J. Harden, K. Manies, M. Mack, and M. -Turetsky. 2010. A dynamic organic soil biogeochemical model for simulating -the effects of wildfire on soil environmental conditions and carbon dynamics -of black spruce forests. Journal of Geophysical Research-Biogeosciences 115. -https://doi.org/10.1029/2010jg001302 - -Yuan, F. M., S. H. Yi, A. D. McGuire, K. D. Johnson, J. Liang, J. W. Harden, -E. S. Kasischke, and W. A. Kurz. 2012. Assessment of boreal forest historical -C dynamics in the Yukon River Basin: relative roles of warming and fire -regime change. Ecological Applications 22:2091–2109. -https://doi.org/10.1890/11-1957.1 - -Zhuang, Q., A. D. McGuire, J. M. Melillo, J. S. Clein, R. J. Dargaville, D. -W. Kicklighter, R. B. Myneni, J. Dong, V. E. Romanovsky, J. Harden, and J. E. -Hobbie. 2003. Carbon cycling in extratropical terrestrial ecosystems of the -Northern Hemisphere during the 20th century: a modeling analysis of the -influences of soil thermal dynamics. Tellus Series B-Chemical and Physical -Meteorology 55:751–776. -https://doi.org/10.3402/tellusb.v55i3.16368 - -Zhuang, Q., A. D. McGuire, K. P. O’Neill, J. W. Harden, V. E. Romanovsky, and -J. Yarie. 2003. Modeling soil thermal and carbon dynamics of a fire -chronosequence in interior Alaska. Journal of Geophysical Research: -Atmospheres 108. -https://doi.org/10.1029/2001jd001244 - -Zhuang, Q., J. M. Melillo, D. W. Kicklighter, R. G. Prinn, A. D. McGuire, P. -A. Steudler, B. S. Felzer, and S. Hu. 2004. Methane fluxes between -terrestrial ecosystems and the atmosphere at northern high latitudes during -the past century: A retrospective analysis with a process-based -biogeochemistry model. Global Biogeochemical Cycles 18. -https://doi.org/10.1029/2004GB002239 +.. bibliography:: + :all: + :style: plain \ No newline at end of file diff --git a/docs_src/sphinx/source/running_dvmdostem.rst b/docs_src/sphinx/source/running_dvmdostem.rst index 1fd92e77..596b81de 100644 --- a/docs_src/sphinx/source/running_dvmdostem.rst +++ b/docs_src/sphinx/source/running_dvmdostem.rst @@ -412,8 +412,68 @@ Parallel Options ================================== Processing Outputs ================================== + + WRITE THIS.... + +------------------ +Output Selection +------------------ + WRITE THIS... + +.. note:: draft thoughts: + NetCDF outputs are specified in a csv file named in config/config.js. The + csv file specifies a variable name (for identification only - it does not + correspond to the variable name in the code), a short description, units, + and what level of detail to output on (timestep and variable part). + [Link to default file after PR merge] Variable name, Description, + Units, Yearly, Monthly, Daily, PFT, Compartment, Layer, + Example entry: VEGC,Total veg. biomass C,gC/m2,y,m,,p,c,, + This will output VegC every month, and provide both PFT and PFT + compartment values. + The file is more user-friendly when viewed in a spreadsheet. + [example] + A complete list of output combinations is below + The initial list of outputs can be found at Issue #252 + LAYERDEPTH, LAYERDZ, and LAYERTYPE should be automatically output if + the user specifies any by-layer output. They are not currently, so ensure + that they are specified on the same timestep as the desired output. + HKLAYER, LAYERDEPTH, LAYERDZ, LAYERTYPE, TCLAYER, TLAYER, and VWCLAYER + must have the layer option specified or they will generate NetCDF + dimension bound errors. + + +------------- +Process +------------- + WRITE THIS... + +.. note:: draft thoughts: + A single output file will be produced for each entry in the specifying file, + based on variable name, timestep, and run stage. + VEGC_monthly_eq.nc + At the beginning of the model run, an output file will be constructed for each + variable specified, for each run stage where NetCDF output is indicated and that + has more than 0 years of run time. + Currently the model tracks the variables specified for each timestep as separate + sets (i.e. monthly separate from yearly, etc). This reduces the number of map + lookups every time the output function is called, but increases the number of + monthly vs. yearly string comparisons. + +------------------------------ +Variable Output Combinations +------------------------------ WRITE THIS... +.. note:: draft thoughts: + '-' indicates that the combination is not an option 'x' indicates that the + combination has been implemented in the code '?' indicates that it is undecided + if the combination should be made available, or that structure in the code needs + to be modified to make data available for output. + Three variables should be automatically written out if any by-layer variable is + specified: Layer type Layer depth Layer thickness Currently they are written out + like standard variables. Automation will need to be added in the future. + + ================================== Processing Inputs ================================== diff --git a/docs_src/sphinx/source/software_development_info.rst b/docs_src/sphinx/source/software_development_info.rst index f1491806..ca75b8fe 100644 --- a/docs_src/sphinx/source/software_development_info.rst +++ b/docs_src/sphinx/source/software_development_info.rst @@ -115,7 +115,8 @@ To build the Sphinx documentation (this document) locally, then do the following .. code:: shell $ make clean - $ PYTHONPATH="/work:/work/calibration:$PYTHONPATH" make html + $ export PYTHONPATH="/work:/work/scripts:/work/scripts/util:/work/calibration:$PYTHONPATH" + $ make html The resulting files are in the ``docs_src/sphinx/build/html`` directory and can @@ -256,8 +257,8 @@ image to render, directly from Google Docs when someone loads the page: .. code:: html - - + + If the original Google Drawing is updated, then the drawing seen in the wiki will be updated too. Take caution with the permissions granted for editing @@ -267,14 +268,14 @@ on the original drawing! When you are editing an image that is embedded, the edits are automatically live on the published website! This is fine for quick edits such as fixing a - typo, but for anything more substantial, it is reccomended that you make a + typo, but for anything more substantial, it is recommended that you make a duplicate of the Google Drawing, edit the duplicate and then copy it back over the original. This will keep your edits from showing up on the live site until you are done with them! .. warning:: - Soure drawings for this document should probably be stored in the + Soucre drawings for this document should probably be stored in the Shared Google Drive so that they are not tied to an individual's account. In Google Docs, there is a way to insert a Google Drawing from a menu: diff --git a/requirements_general_dev.txt b/requirements_general_dev.txt index 665aeda0..dddf9101 100644 --- a/requirements_general_dev.txt +++ b/requirements_general_dev.txt @@ -6,14 +6,18 @@ netCDF4==1.5.8 commentjson==0.9.0 ipython==8.10.0 jupyter==1.0.0 -jupyter-sphinx==0.4.0 lhsmdu==1.1 -Sphinx==5.1.1 -sphinx-rtd-theme==1.1.0 -sphinx-toolbox==3.4.0 -sphinx-argparse==0.4.0 xarray==2023.1.* pypdf==5.1.* # for SA - maybe merits its own file?? scikit-learn + +# For building documentation +Sphinx==5.1.1 +sphinx-rtd-theme==1.1.0 +sphinx-toolbox==3.4.0 +sphinx-argparse==0.4.0 +sphinxcontrib-bibtex +jupyter-sphinx==0.4.0 +